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Samiran Dey, Indian Association for the Cultivation of Science, Kolkota.
Tuesday 14 April 2026, 14:30-15:30
dak33's list
A personal list of talks.
Contact: David Knowles
3 upcoming talks View 2572 archived talks
MRC Biostatistics Unit Seminars
BSU Seminar: "Generating crossmodal gene expression from cancer histopathology improves multimodal AI predictions"
⚠️ This will be a free hybrid seminar. To register to attend remotely, please click here: https://cam-ac-uk.zoom.us/meeting/register/MSeOkbjoRr2eCc1JQaumTQ
MRC Biostatistics Unit Seminars
BSU Seminar: "Nonparametric causal decomposition of group disparities"
⚠️ This will be a free hybrid seminar. To register to attend remotely, please click here: https://cam-ac-uk.zoom.us/meeting/register/4GWLKVphSsu3k4a4D_dreQ
MRC Biostatistics Unit Seminars
BSU Seminar: "A unifying framework for generalised Bayesian online learning in non-stationary environments"
⚠️ This will be a free hybrid seminar. To register to attend remotely, please click here: https://cam-ac-uk.zoom.us/meeting/register/W8Gl6_hoQ7mUob4Rh8miIA
Machine Learning Reading Group @ CUED
From Stochastic Interpolants to Flow Maps: Foundations, Fast Generation, and Applications to Weather & Climate Modeling
Seminars on Quantitative Biology @ CRUK Cambridge Institute
How life finds a way: resilience in mammalian embryogenesis
Machine Learning Reading Group @ CUED
Evolution Strategies at the Hyperscale
Machine Learning Reading Group @ CUED
Evolution Strategies at the Hyperscale
Peter Whittle Lecture
The role of Random Matrix Theory for the optimization algorithms of Machine Learning
Machine Learning Reading Group @ CUED
Machine Learning on Tabular Data
Machine Learning Reading Group @ CUED
Rethinking aleatoric and epistemic uncertainty
MRC Biostatistics Unit Seminars
BSU Seminar: "New Bayesian methods and tools to address health challenges"
⚠️ This will be a free hybrid seminar. To register to attend remotely, please click here: https://cam-ac-uk.zoom.us/meeting/register/7KTIPoNBSVuPXcFtZh8MiQ
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The role of Selenoprotein O in mitochondrial signaling
Statistics
Minimax rate for multivariate data under componentwise local differential privacy constraints
Statistics
Towards multi-purpose locally differentially-private synthetic data release via plug-in estimation
MRC Biostatistics Unit Seminars
BSU Seminar: "Genomic newborn screening, and how to evaluate it"
⚠️ This will be a free hybrid seminar. To register to attend remotely, please click here: https://cam-ac-uk.zoom.us/meeting/register/0erNJSr0T2OKXJE4uYYgHQ
Statistics
The Geometry of Random Neural Networks
MRC Biostatistics Unit Seminars
BSU Seminar: "Graphical models for missing data not at random: identification, inference, and imputation"
⚠️ This will be a free hybrid seminar. To register to attend remotely, please click here: https://cam-ac-uk.zoom.us/meeting/register/y-ukrQxwTLGSoGtSGiGUkA
Machine Learning Reading Group @ CUED
How does gradient descent work?
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Expanding the kinome
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Hard numbers—physicochemical models of a mitotic signalling organelle
Statistics
Valid F-screening in linear regression
Machine Learning Reading Group @ CUED
Variational Inference: An Algorithm-Centric Perspective
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Modular strategies to decode and rewire cell surface signaling
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Modular strategies to decode and rewire cell surface signaling
Machine Learning Reading Group @ CUED
Neural Operators for Scientific Simulation
MRC Biostatistics Unit Seminars
BSU Seminar: "Robust and conjugate Gaussian processes"
⚠️ This will be a free hybrid seminar. To register to attend remotely, please click here:https://cam-ac-uk.zoom.us/meeting/register/oURXKjAISECZrOvFPRw0Mw
Statistics
The manifold hypothesis in science & AI
Machine Learning Reading Group @ CUED
A Tutorial on Algorithmic Information Theory in Modern ML
MRC Biostatistics Unit Seminars
BSU Seminar: "Predictive resampling for scalable Bayes"
⚠️ This will be a free online seminar. To register to attend, please click here: https://cam-ac-uk.zoom.us/meeting/register/gELlOqxOT3imWtS8MRVYRw
Machine Learning Reading Group @ CUED
Diffusion Language Models
Statistics
Universal Copulas
Machine Learning Reading Group @ CUED
An Introduction to Stochastic Interpolants
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Zero-shot design of drug-binding proteins using neural networks
Statistics
Geometric extremal graphical models
MRC Biostatistics Unit Seminars
BSU Seminar: "Effective Health Technologies Faster? Value-Based, Response Adaptive Learning in Clinical Trials"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/IMAzE11MRtyNkOGZpkv4GA
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Cells, Tissues & Organs: assembling the Human Cell Atlas
MRC Biostatistics Unit Seminars
BSU Seminar: "Upgrading survival models with CARE"
⚠️ This will be a free hybrid seminar. To register to attend remotely, please click here: https://cam-ac-uk.zoom.us/meeting/register/M66a6T77T9-0PCylnJfB7g
MRC Biostatistics Unit Seminars
BSU Seminar: "Upgrading survival models with CARE"
⚠️ This will be a free hybrid seminar. To register to attend remotely, please click here: https://cam-ac-uk.zoom.us/meeting/register/M66a6T77T9-0PCylnJfB7g
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Multi-modal modeling in precision medicine: from data imputation to synthetic data
MRC Biostatistics Unit Seminars
BSU Seminar: "Predictive Polygenic Scores: Considerations and an Example"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/2-jzYw6UQ0uzKp5LpplBhg
Cambridge Statistics Clinic
Statistics Clinic Summer 2025 II
Machine Learning Reading Group @ CUED
The structure of curvature in neural networks
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Quantitative Biology Seminar
Machine Learning Reading Group @ CUED
Variational Uncertainty Decomposition for In-Context Learning
Machine Learning Reading Group @ CUED
Variational Uncertainty Decomposition for In-Context Learning
Machine Learning Reading Group @ CUED
Vision-language models (VLMs)
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
Vision-language models (VLMs)
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Statistics
Complexity of sampling truncated log-concave measures, and the role of stochastic localization
Machine Learning Reading Group @ CUED
Conditional Expectation and Machine Learning
Machine Learning Reading Group @ CUED
Evaluating and Regulating Foundation Models
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "AI for the Human Cell Atlas"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/jy1cAVg4SeiEB-grYmQV8Q
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Quantitative Biology Seminar
MRC Biostatistics Unit Seminars
BSU Seminar: "A Regression Tree Approach to Missing Data"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/j/81415700586?pwd=7rhWD5jDWlkAq1nuMUPDJGDkhQsMCM.1
MRC Biostatistics Unit Seminars
BSU Seminar: "Investigating complex dependence structures using Bayesian mixture modelling"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/7PLSTFN7QM6iUvdzQaegEw
MRC Biostatistics Unit Seminars
BSU Seminar: "Common atoms mixture models in some biostatistical inference problems"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/4uUskN5ZQjaJzckpMbxQ1Q
Seminars on Quantitative Biology @ CRUK Cambridge Institute
QBS
Machine Learning Reading Group @ CUED
Out-of-context reasoning/learning in LLMs and its safety implications
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Engineering genomes and proteomes as foundational biotechnology for translational research
Machine Learning Reading Group @ CUED
Learning to See the World in 3D
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "A Nonparanormal Approach to Marginal Inference"
⚠️ This will be a free online seminar. To register to attend, please click on the link: https://cam-ac-uk.zoom.us/webinar/register/WN_xwbSLwLITemQeb8b-jk-Fg
Machine Learning Reading Group @ CUED
An Introduction to In-Context Learning
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "Reclassification of multiple sclerosis using probabilistic machine learning"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click on this link: https://cam-ac-uk.zoom.us/webinar/register/WN_0cu2ldnhQhKdTBNWL6Mo1A
MRC Biostatistics Unit Seminars
BSU Seminar: "Reclassification of multiple sclerosis using probabilistic machine learning"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click on this link: https://cam-ac-uk.zoom.us/webinar/register/WN_0cu2ldnhQhKdTBNWL6Mo1A
Peter Whittle Lecture
Algorithmic stability for regression and classification
Machine Learning Reading Group @ CUED
ML for Medium-Range Weather Forecasting
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
Influence Functions
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
Sampling with diffusion models
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Generative machine learning to model cellular perturbations
Machine Learning Reading Group @ CUED
Geometric Deep Learning for Structure-Based Drug Design
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Statistics
Gaussian and non-Gaussian universality, with applications to data augmentation
⚠️ Note unusual location
Machine Learning Reading Group @ CUED
Diffusion Models Beyond Mean Prediction
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "The Lifebelt Particle Filter: a novel robust SMC scheme"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/webinar/register/WN_WSJRt7ZlSTimpffcfcd6WA
MRC Biostatistics Unit Seminars
BSU Seminar: "The Lifebelt Particle Filter: a novel robust SMC scheme"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/webinar/register/WN_WSJRt7ZlSTimpffcfcd6WA
Statistics
Identification and Estimation of Graphical Continuous Lyapunov Models
⚠️ Note unusual location
Machine Learning Reading Group @ CUED
Unpacking UK’s New AI Action Plan: Ambition versus Reality
⚠️ Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "Efficient Sequential Experimentation: Bridging Model-Based Reinforcement Learning and Bayesian Optimal Experimental Design"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/webinar/register/WN_GS1_Dn3SQXydSuW9p3oNnQ
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Steering the evolutionary dynamics of cancer through space and time
Machine Learning Reading Group @ CUED
An Introduction to Algorithmic Differentiation
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
An Introduction to Algorithmic Differentiation
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The Roles of the Epilepsy-Associated Kinase CDKL5
Machine Learning Reading Group @ CUED
Foundation Models in Robotics
MRC Biostatistics Unit Seminars
BSU Seminar: "Graphical and summary diagnostics for node level adequacy in Bayesian hierarchical models"
⚠️ This will be a free online seminar using Zoom Webinar. Register using this link: https://cam-ac-uk.zoom.us/webinar/register/WN_AbR8yEMdQKGtBfxJbbEeNQ
Seminars on Quantitative Biology @ CRUK Cambridge Institute
How to Fold Every Protein: (Mission Accomplished?)
Machine Learning Reading Group @ CUED
Learning curve prediction for AutoML
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
Learning curve prediction for AutoML
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "Personalized Decision-Making for Infectious Disease Control: Causal Inference and Complex Dependence"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZAtcuCpqT8oGtciL4QahuHDVi2_-NRp9enh
Machine Learning Reading Group @ CUED
An Elementary Introduction to Sequential Monte Carlo Samplers
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Protein Evolution in Sequence Landscapes - From Data to Models and Back
Machine Learning Reading Group @ CUED
Scalable Sampling Using Annealed Algorithms
MRC Biostatistics Unit Seminars
BSU Seminar: "IV-learner: learning conditional average treatment effects using instrumental variables"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZ0od-CorDouHdEyadWd2HkaL_HUObpPwuoJ
Machine Learning Reading Group @ CUED
Are we making progress in unlearning?
Machine Learning Reading Group @ CUED
Natural Experiments in NLP and Where to Find Them
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "Multi-state modelling to estimate infectious disease burden"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZMpf-6gpjkvHNaHjyzJDmLJi7vIrRb-STIQ
Machine Learning Reading Group @ CUED
Linear Attention for Efficient Transformers
Statistics
Valid Heteroskedasticity Robust Testing
MRC Biostatistics Unit Seminars
BSU Seminar: "Graphical and summary diagnostics for node level adequacy in Bayesian hierarchical models"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZwkf-ysqDgqG9W5MbRoGxq5re7R9XadbBBd
MRC Biostatistics Unit Seminars
BSU Seminar: "Bayesian latent multi-state modelling for longitudinal health trajectories"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZIqcuutqTkoG9R7enI9iOHBr61dOjW5BTKl
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Protein genetic architecture is simple, and epistasis can facilitate the evolution of new functions
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Quantitative Biology Seminar
⚠️ **Seminar cancelled**
Statistics
Treatment Effects in Market Equilibrium
MRC Biostatistics Unit Seminars
BSU Seminar: "Bayesian nonparametric spectral analysis of multivariate time series"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZMrdOmpqzMuHNHNuAnIvofAmb7HOCQIQwzW
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Digital Cancer Twins: From Mechanistic Insights to Therapeutic Applications
Machine Learning Reading Group @ CUED
Task Alignment
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "A Bayesian framework for incorporating exposure uncertainty into health analyses with application to air pollution and stillbirth"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://events.teams.microsoft.com/event/22b7f255-8f6c-4dce-9c83-36281a3261bf@513def5b-df17-4107-b552-3dba009e5990
Machine Learning @ CUED
Application of the optimal transport Gromov-Wasserstein problem to manifold learning and graph analysis
Machine Learning @ CUED
Application of the optimal transport Gromov-Wasserstein problem to manifold learning and graph analysis
Machine Learning @ CUED
Application of the optimal transport Gromov-Wasserstein problem to manifold learning and graph analysis
Statistics
Oja's algorithm for sparse PCA
Statistics
Learning with latent symmetries
Machine Learning Reading Group @ CUED
A Light Introduction to Topological Data Analysis
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "The Topological Properties of the Protein Universe"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://events.teams.microsoft.com/event/93edb3b5-eb5d-4d19-b30b-1526233e3c17@513def5b-df17-4107-b552-3dba009e5990
MRC Biostatistics Unit Seminars
BSU Seminar: "Making predictions under intervention to avoid causal blind spots in treatment decisions"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://events.teams.microsoft.com/event/7045e477-b689-46bc-9ec3-fe1ed827a158@513def5b-df17-4107-b552-3dba009e5990
Statistics
Rates of convergence for tensor denoising
Machine Learning Reading Group @ CUED
Mean Field Theory of NNs
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Programmed evolution: Using asexual gene drives to sculpt tumor populations and combat genetic diversity
Machine Learning Reading Group @ CUED
Discussing the Stanford AI Report
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
Discussing the Stanford AI Report
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
AI Control
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
Neural likelihood-free inference
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Screening Approaches for the Identification of Covalent Peptide Inhibitors
MRC Biostatistics Unit Seminars
BSU Seminar: “Bayesian behavioural-change epidemic models: is your population alarmed?”
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZ0vceqsqDwtHNLalYuBk7GmojclSXN5wIcE
Machine Learning Reading Group @ CUED
An Introduction to the Conjugate Gradient Method
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Statistics
Concentration and Free Probability
MRC Biostatistics Unit Seminars
BSU Seminar: "Using Joint Models for Longitudinal and Time-to-Event Data to Investigate the Causal Effect of Salvage Therapy after Prostatectomy"
⚠️ This will be a free online seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZclceGorT0qE9YE3YCcRSFhCPPH_6ZNFPgh
Computational and Systems Biology Seminar Series 2023 - 24
Mathematical modelling to develop insights into cancer evolution
MRC Biostatistics Unit Seminars
BSU Seminar: "Uncertainty Quantification in the Digital Medicine Era"
⚠️ This will be a free hybrid event. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZAsduitrTotGNZxFmtFPPAx6Jh2LZfCYbV3
Machine Learning Reading Group @ CUED
An Introduction to Transformer Neural Processes
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Cell size - A new hallmark of aging?
Machine Learning @ CUED
Consistent Validation for Predictive Methods in Spatial Settings
Computational and Systems Biology Seminar Series 2023 - 24
Mapping DNA replication stress in cancer cells and parasites with long-read sequencing and AI
Machine Learning Reading Group @ CUED
Learning Symmetries in Neural Networks
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "Statistical modelling for state-of-the-art gene editing experiments"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZcqdOmqqzsuE9HyOT32ptW3DZiTCmkZT-3X#/registration
Computational and Systems Biology Seminar Series 2023 - 24
Modelling Blood Cell Development across Molecular and Tissue Scales
Machine Learning Reading Group @ CUED
GenCast: Diffusion-based ensemble forecasting for medium-range weather (or: How to ruin a numerical weather forecaster’s Christmas)
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "Graphical and summary diagnostics for node level adequacy in Bayesian hierarchical models"
⚠️ This will be a free online seminar. To register to attend, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZYocuCvpjotHNQoiEBwivER-WSnaKd-IlFw
Computational and Systems Biology Seminar Series 2023 - 24
Horizonal gene transfer in transmissible cancers
Machine Learning Reading Group @ CUED
Bayesian coresets
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Functional studies of genetic variation using precision genome editing
MRC Biostatistics Unit Seminars
BSU Seminar: "Semiparametric posterior corrections"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZIqd-quqjkiHtRsIwSM3Sec0QFfHrtRftXa
Statistics
Response-adaptive randomization in clinical trials: from myths to practical considerations
MRC Biostatistics Unit Seminars
BSU Seminar: "Causal machine learning for biomarker subgroup discovery in randomised trials".
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://cam-ac-uk.zoom.us/meeting/register/tZ0rf-qppzwsEtEisA_2ZCkA3KoJ3d53uW1P
MRC Biostatistics Unit Seminars
BSU Seminar: "Hyper-Localization and Predictive Modeling of Rapid Lung Function Decline in Cystic Fibrosis"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZ0qdOyurDkjHdO0RzdaqWctUrYMks1YPvY1
MRC Biostatistics Unit Seminars
BSU Seminar: "Unravelling the mechanisms and decision-making logic of biological systems"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZwtdOisrTosGNIMVJIXmGuq2X_so_tpo7s6
Machine Learning Reading Group @ CUED
Flow matching, stochastic interpolants and everything in between
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning @ CUED
Modern Bayesian Experimental Design
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Exploring cell heterogeneity in health and disease using single-cell proteomics and transcriptomics
Machine Learning Reading Group @ CUED
Challenges of Regulating Increasingly Complicated Human-AI Collaborative Systems
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "A new frequentist implementation of the Daniels and Hughes bivariate meta-analysis model for surrogate outcomes"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click on this link: https://us02web.zoom.us/meeting/register/tZAqcuuurzIuGtEUj6y8h6vKpM1Krt5hj60L
Machine Learning Reading Group @ CUED
A Poisson Process Model for Monte Carlo
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "Harnessing Extra Randomness: Replicability, Flexibility and Causality"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZAofuihqzgvHNyG24AgAAytgHlr1nmpetpx
Statistics
Nonparametric Statistics for SPDEs
Machine Learning Reading Group @ CUED
Learning Directed Acyclic Graphs (DAGs) With Continuous Optimization
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
Deep Learning for Medium-Range Global Weather Prediction
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Statistics
Adaptive two-sample testing
Machine Learning Reading Group @ CUED
Learning linear models in-context with transformers
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: "Dynamic survival analysis: modelling the hazard function via ordinary differential equations"
⚠️ This will be a free hybrid event. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZYlce-spjIqHdQ4PYgBuSHSUSDRmLBAJQ5n
Seminars on Quantitative Biology @ CRUK Cambridge Institute
TBC
Peter Whittle Lecture
A new coefficient of correlation
Machine Learning Reading Group @ CUED
Quasi-Monte Carlo: structure in the randomness for better sampling
MRC Biostatistics Unit Seminars
BSU Seminar: 'Some advances and applications of robust gradient-based Markov chain Monte Carlo'
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZUsdOypqTwrH9LeiEEIL8dXxO_IpOC8lVMS
Machine Learning @ CUED
Visit and talk by Jay McClelland: "Some thoughts on the differences between human and machine intelligence"
Machine Learning @ CUED
Compositional mathematics and automatic gradient descent
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Studying human oncoproteins beyond cancer: lessons learned from the RAS GTPases
Machine Learning Reading Group @ CUED
Deciphering Batch Effects in Single-cell Transcriptomics with Concept Bottlenecks
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
Schrödinger bridges, diffusion and SDEs
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Statistics
Response-adaptive randomization in clinical trials: from myths to practical considerations
⚠️ Canceled
Machine Learning Reading Group @ CUED
The LLM Tidal Wave
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
The LLM Tidal Wave
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
Game theory, distributional reinforcement learning, control and verification
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: 'Bayesian analysis of diffusion-driven multi-type epidemic models with application to COVID-19'
⚠️ This will be an online seminar. To register to attend, please click on this link: https://us02web.zoom.us/meeting/register/tZ0ocO6qrTsiH9V3mlmvd_EOYT1sTBOKOmUZ
Machine Learning Reading Group @ CUED
On choosing the mass matrix for Hamiltonian Monte Carlo
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Statistics
Randomized and exchangeable improvements of Markov's, Chebyshev's and Chernoff's inequalities
Machine Learning Reading Group @ CUED
Reward Modelling
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
MRC Biostatistics Unit Seminars
BSU Seminar: 'Modelling the response to vaccine in non-human primates to define SARS-CoV-2 mechanistic correlates of protection'
⚠️ This will be a free online seminar. To register to attend, please click here: https://us02web.zoom.us/meeting/register/tZUuf-usqDovGdf1TbAtYgsGCRJmoz0Hmbfi
Seminars on Quantitative Biology @ CRUK Cambridge Institute
OpenFold: Lessons learned and insights gained from rebuilding and retraining AlphaFold2.
⚠️ On Zoom Only
Computational and Systems Biology
CCBI/C2D3 Computational Biology Annual Symposium
Machine Learning @ CUED
Convergence bounds for the Random Walk Metropolis algorithm - Perspectives from Isoperimetry
Machine Learning Reading Group @ CUED
Navigating the Future: Upcoming EU AI Regulation and its Potential Impact on the Field
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Machine Learning Reading Group @ CUED
Learning-based multiscale modeling: computing, data science, and uncertainty quantification
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
CCIMI Seminars
Fundamental limits of generative AI
Machine Learning Reading Group @ CUED
Neural Tangent Kernel
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders.
MRC Biostatistics Unit Seminars
BSU Seminar: 'Covariate Adjustment in Randomized Experiments with Incomplete Covariate and Outcome Data'
Machine Learning Reading Group @ CUED
No-regret Dynamics for Multi-agent Learning
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders.
Machine Learning Reading Group @ CUED
Scalable Approaches to Self-Supervised Learning using Spectral Analysis
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders.
Machine Learning Reading Group @ CUED
Physics-informed machine learning
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Oncogene-like addiction to aneuploidy in human cancers
Machine Learning Reading Group @ CUED
Causal Machine Learning
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Computational and Systems Biology Seminar Series 2023 - 24
Finding Target-Disease-Drug evidences from Literature and supporting curators. Please note: the details of this talk have changed
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
User Manipulation in Recommender Systems
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.
Computational and Systems Biology Seminar Series 2023 - 24
Discovering the gene networks that regulate hunger
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
Random Features for Kernel Approximation
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders.
MRC Biostatistics Unit Seminars
BSU Seminar: 'Methods for Bayesian optimal design of experiments, with application in biological science’
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZcrd-uoqjMiGN3f68WQc7zJQ7LmM4sZa2rx
Computational and Systems Biology Seminar Series 2023 - 24
Computational Biology in Drug Discovery
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
An Overview of Differential Privacy, Membership Inference Attacks, and Federated Learning
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders.
Computational and Systems Biology Seminar Series 2023 - 24
Seeing the Unseen
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
Bayesian Neural Networks
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders.
MRC Biostatistics Unit Seminars
BSU Seminar: 'Bayesian Covariance Structure Modelling of Clinical Trial Data'
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZcpf-uvrDMiGtLpMKemoVfOPmiD91Ju0-Xq
Computational and Systems Biology Seminar Series 2023 - 24
Mapping DNA replication stress in parasites and cancer cells with long-read sequencing and AI
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
Offline Reinforcement Learning
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders.
MRC Biostatistics Unit Seminars
BSU Seminar: 'From Data to Decisions: Causal Inference Motivated by Policy Questions'
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click on this link: https://us02web.zoom.us/meeting/register/tZwodOytqjItGNL_he9tZXSxmdT7KTWWQRgF
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Mammalian Synthetic Biology – Biomolecular Circuits as Medicine
Statistics
The Kalman-Bucy filter revisited: Mean-field equations & duality
⚠️ Joint Statistics and CCIMI Seminar (note unusual time)
Computational and Systems Biology Seminar Series 2023 - 24
Research in the Goldman group: pandemic-scale phylogenetics, and optimizing new sequencing technologies
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
{PF}^2ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimization Under Unknown Constraints
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders.
Statistics
Counterfactual fairness (CANCELLED)
Computational and Systems Biology Seminar Series 2023 - 24
Does computational biology explain Fibonacci numbers in plants?
⚠️ Meetings are planned to take place in person. Seminars are principally for MPhil students. Please email the adminstrator should you wish to attend as a guest
MRC Biostatistics Unit Seminars
BSU Seminar: 'Phases of research for statistical methods’
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZEtd--hrzItHtTIezm0p763Lsc95VI0Q254
Machine Learning @ CUED
Calls to F the Algorithm: Lessons from the 2020 Exam Debacle
Computational and Systems Biology Seminar Series 2023 - 24
Computational image analysis for coeliac disease diagnosis
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
MRC Biostatistics Unit Seminars
BSU Seminar: 'Detecting National, Regional and Global Changes in Terror Activity'
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click on this link: https://us02web.zoom.us/meeting/register/tZMtf-iqrjoiGd3egbADJAIx6u477THr4Et9
Computational and Systems Biology Seminar Series 2023 - 24
Bioinformatic analysis of T-cell antigen receptors as a novel diagnostic test for coeliac disease/ gluten sensitivity
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
MRC Biostatistics Unit Seminars
BSU Seminar: "Statistical approaches for differential analyses on transcriptomics data"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZYkfuivpj0jEta0t6wA4iKlz8YOaojvNwdt
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Mapping somatic evolution with single-cell multi-omics
MRC Biostatistics Unit Seminars
BSU Seminar: 'Double soft-thresholded model for multi-group scalar on vector-valued image regression'
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click on this link: https://us02web.zoom.us/meeting/register/tZIucOmvrj4pHd3vnOm5ReIZ1wmXR9x-xC1z
Machine Learning Reading Group @ CUED
Scalable simulation and inference in non-Gaussian stochastic PDEs
Machine Learning @ CUED
Scalable simulation and inference in non-Gaussian stochastic PDEs
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Interpretable Neural Networks for Computer Vision: Clinical Decisions that are Computer-Aided, not Automated
Computational and Systems Biology Seminar Series 2023 - 24
Motile behaviour and evolution of bacteria in antibiotic landscapes
⚠️ Meetings are planned to take place in person. Seminars are principally for MPhil students. Please email the adminstrator should you wish to attend as a guest
Seminars on Quantitative Biology @ CRUK Cambridge Institute
On the Evolutionary History of Metastatic Cancer
Statistics
Biostatistics: successes, challenges and opportunities
⚠️ Unusual starting time to accommodate a special tea event after the seminar
Machine Learning @ CUED
Measuring Alignment Between Perceptual Systems: An Analysis Through The Lens of Shared Invariances
Machine Learning Reading Group @ CUED
Information Geometry — Natural Gradient Descent
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders.
MRC Biostatistics Unit Seminars
BSU Seminar: “Using Electronic Health Records for Scientific Research: Promises and Perils”
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZctduyqrjgsEtYxJkz-fTWdzMmjL7qFrnAC
Machine Learning @ CUED
Gaussian processes, spectral analysis kernels and optimal transport
Machine Learning @ CUED
Deep Reinforcement Learning for Multi-Agent Interaction
Computational and Systems Biology Seminar Series 2023 - 24
Knowledge Graphs for Precision Oncology
⚠️ Meetings are planned to take place in person. Seminars are principally for MPhil students. Please email the adminstrator should you wish to attend as a guest
Machine Learning Reading Group @ CUED
Predicting generalization of ML models.
⚠️ Zoom link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders.
MRC Biostatistics Unit Seminars
BSU Seminar: "The HealthGap study: Using linked administrative data to understand cardiovascular health of Indigenous people living in Victoria, Australia"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZMpc-qtqD4iHtMcJUj5fiD4uVwRqMWP4XkI
Machine Learning @ CUED
Presenting Hawk-Eye’s Skeletrack: Our machine learning approach to building a real time skeletal tracking system for sports, and how we're using it to shape the future of fan engagement
MRC Biostatistics Unit Seminars
BSU Seminar: "Derivative-Based Neural Modelling of Cumulative Distribution Functions for Survival Analysis"
⚠️ This will be a free online seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZIqdu6gpjgrHd1yp38Mi3xQxgCg_5BOQThO
Computational and Systems Biology Seminar Series 2023 - 24
Transmissible cancers: when cancer cells become infectious agents?
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator.
Machine Learning Reading Group @ CUED
A tutorial on diffusion models
Statistics
Local Independence Graphs
Computational and Systems Biology Seminar Series 2023 - 24
Principles of Protein Structural Ensembles Determination
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
MRC Biostatistics Unit Seminars
BSU Seminar: "Making all pairwise comparisons in multi-arm clinical trials without control treatment"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here:https://us02web.zoom.us/meeting/register/tZMlc-Grrj0vHNCSqPPY92EKkTJG5Xjm5yhY
Peter Whittle Lecture
Resampling methods for networks
Computational and Systems Biology Seminar Series 2023 - 24
Buffering genetic variation in populations
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
Benchmarking and evaluation in contemporary machine learning
Seminars on Quantitative Biology @ CRUK Cambridge Institute
TALK POSTPONED
Computational and Systems Biology Seminar Series 2023 - 24
A semantics knowledge commons for climate change
⚠️ Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
MRC Biostatistics Unit Seminars
Virtual BSU Seminar: "Variable Selection and Prioritization in Bayesian Machine Learning Methods"
⚠️ This will be a free virtual seminar. To register, please click here: https://us02web.zoom.us/meeting/register/tZIlc--rrT8qGNMFApbQ8304Icj6vW4CDcFo
Statistics
Comparison of Markov chains via weak Poincaré inequalities, with application to pseudo-marginal MCMC
Computational and Systems Biology Seminar Series 2023 - 24
An introduction to counts-of-counts data
⚠️ Meetings are planned to take place in person. Seminars are principally for MPhil students. Please email the adminstrator should you wish to attend as a guest
Machine Learning Reading Group @ CUED
Advanced artificial agents intervene in the provision of reward
Statistics
Long Story Short: Omitted Variable Bias in Causal Machine Learning
⚠️ Statistics and CCIMI seminar, followed by a drinks reception
Machine Learning Reading Group @ CUED
Theory and Practice of Infinitely Wide Neural Networks - Guest Talk
MRC Biostatistics Unit Seminars
BSU Seminar: "Genome-wide genetic models for association, heritability analyses and prediction"
⚠️ This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZcpcuipqTMuGtP_pIJrVQDLQGbP3ndqAh-N
MRC Biostatistics Unit Seminars
BSU Seminar: "Challenges in risk prediction using routinely collected health data"
⚠️ This will be a free online seminar. To register, click here: https://us02web.zoom.us/meeting/register/tZEkdOupqDspHtK1D30gXlBykdbIvLV8DMdH
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Combining multi-omics and biological knowledge to extract disease mechanisms
⚠️ Please contact Ciara for further details
Machine Learning Reading Group @ CUED
The unreasonable effectiveness of mathematics in large scale deep learning
MRC Biostatistics Unit Seminars
BSU Seminar: "Design and Inference for Enrichment Trials with a Continuous Biomarker"
⚠️ This will be a hybrid seminar. If you would like to attend virtually, please register for free here - https://us02web.zoom.us/meeting/register/tZErduCprzwiEtQhPshDBMXcqhwlvdZtp_IP
Machine Learning Reading Group @ CUED
The role of meta-learning for few-shot classification
Machine Learning @ CUED
Noise-Aware Differentially Private Synthetic Data
Machine Learning Reading Group @ CUED
Benefits and Shortcomings of Assistance
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Deciphering Shared Intratumor Transcriptional Heterogeneity of Human Tumors
Machine Learning @ CUED
Estimating RSV seasonality from pandemic disruptions: a modelling study
Machine Learning Reading Group @ CUED
Discussion: Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors
MRC Biostatistics Unit Seminars
BSU Seminar: “Optimising the discovery and development of gene silencing drugs with genetics and genomics”
⚠️ This will be a virtual seminar. To register for free, please click here: https://us02web.zoom.us/meeting/register/tZEudeGqrDgpH9w6XLGADT0ZoJB-ARc5EdD0
Machine Learning Reading Group @ CUED
Discussion: Learning PAC-Bayes Priors for Probabilistic Neural Networks
Machine Learning Reading Group @ CUED
Rethinking evaluation for machine learning models
Machine Learning Reading Group @ CUED
Discussion: Bayesian Model Selection, the Marginal Likelihood, and Generalization
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The Genomic Evolution of Cancer
MRC Biostatistics Unit Seminars
BSU Virtual Seminar: “Group Testing in Structured and Dynamic Networks”
⚠️ This will be a virtual seminar. To register for free, please click here: https://us02web.zoom.us/j/85960970204?pwd=dnVyWUFTSkM1bjJkWGMvc0ViLzA2Zz09
Computational and Systems Biology
CCBI/C2D3 Computational Biology Annual Symposium 2022
Machine Learning @ CUED
Beyond Conformal Prediction: Distribution-Free Uncertainty Quantification for Complex Machine Learning Tasks
Machine Learning Reading Group @ CUED
How close are these distributions? A brief introduction to statistical distances and divergences.
MRC Biostatistics Unit Seminars
BSU Seminar: “Optimal design of First in Human trials via dynamic programming”
⚠️ This will be a hybrid seminar. If you would like to participate virtually, please register using this link: https://us02web.zoom.us/meeting/register/tZwvf-qgrTwrHNMDOZ_UZNN7h-wCbi90t9bA
Machine Learning Reading Group @ CUED
Bests of ICLR
MRC Biostatistics Unit Seminars
BSU Seminar: "Sparse Hamiltonian Flows (or: Bayesian Coresets Without all the Fuss)"
⚠️ This will be a virtual seminar. FREE registration: https://us02web.zoom.us/meeting/register/tZ0rc-2vpz4qHNxdJ4Cm4hyLEn4BVOG5YcIt
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Drug response and tolerance in normal and cancer cells
Machine Learning @ CUED
Graph neural network approach for decentralized multi-robot coordination
Machine Learning Reading Group @ CUED
Machine Learning with Quantum Computers
Machine Learning Reading Group @ CUED
Autoregressive Diffusion Models
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Causality, Perturbations, Gene Regulation, and Drug Repurposing
Machine Learning Reading Group @ CUED
An Overview of AI Alignment
Peter Whittle Lecture
Demystifying Deep Learning
Machine Learning Reading Group @ CUED
The Bayesian Learning Rule for Adaptive AI
Machine Learning Reading Group @ CUED
Introduction to differential privacy
Computational and Systems Biology Seminar Series 2023 - 24
Transmissible cancers: when cancer cells become infectious agents
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Accelerating drug discovery with the power of microscopy & AI
Computational and Systems Biology Seminar Series 2023 - 24
Mining for meaning in electronic health records; deep semantic normalisation for precision medicine and discovery.
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
Retrieval Augmented NLP
Computational and Systems Biology Seminar Series 2023 - 24
Seeing the unseen: informatic approaches to find, characterise and drug conserved regions of nucleic acid in RNA viruses
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
Circuits and Interpretability
MRC Biostatistics Unit Seminars
Virtual BSU Seminar: "A flexible sensitivity analysis for sample selection bias"
⚠️ This will be a virtual seminar. To register for free, please click here: https://www.eventbrite.co.uk/e/bsu-seminar-dr-matt-tudball-tickets-251838374357
Computational and Systems Biology Seminar Series 2023 - 24
Drug Discovery in the era of large-scale genetics and genomics data
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
Optimal Transport Metrics
Computational and Systems Biology Seminar Series 2023 - 24
Machine learning with biomedical ontologies: applications in precision health
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Machine Learning Reading Group @ CUED
Learned Compression
MRC Biostatistics Unit Seminars
Virtual BSU Seminar: "Using Variational Bayes for fast inference in large longitudinal datasets”
⚠️ This will be a free virtual seminar. If you would like to attend, please register here: https://www.eventbrite.co.uk/e/bsu-virtual-seminar-dr-david-hughes-tickets-242962345917
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Genomic and digital pathology approaches to elucidate cancer dormancy
⚠️ Hybrid seminar, please join at: https://zoom.us/j/97592722368?pwd=eXg4bHN3SEJKMm5hRXpCZUtncnVBdz09
Computational and Systems Biology Seminar Series 2023 - 24
Computational image analysis for coeliac disease diagnosis
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator
Statistics
Two-sample testing of high-dimensional linear regression coefficients via complementary sketching
Computational and Systems Biology Seminar Series 2023 - 24
Bioinformatic analysis of T-cell antigen receptors as a novel diagnostic test for coeliac disease/ gluten sensitivity
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator.
Machine Learning Reading Group @ CUED
Diffusion and Score-based Generative Models
Machine Learning Reading Group @ CUED
AI Safety
Machine Learning Reading Group @ CUED
[Cancelled] Best of Neurips
Machine Learning Reading Group @ CUED
Energy-Based Models
Statistics
CANCELLED: Systematic inducement of sparsity
Computational and Systems Biology Seminar Series 2023 - 24
An Introduction to Machine Learning in AstraZeneca
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator.
MRC Biostatistics Unit Seminars
BSU virtual seminar: "Assessing batch effects and their implications in single cell RNA sequencing experiments"
⚠️ This will be a virtual seminar. If you would like to attend, please email alison.quenault@mrc-bsu.cam.ac.uk for the joining information.
Computational and Systems Biology Seminar Series 2023 - 24
Principles of Protein Structural Ensembles Determination
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator.
Machine Learning Reading Group @ CUED
Deep Kernels
Seminars on Quantitative Biology @ CRUK Cambridge Institute
MAGNATM, a novel single molecule platform to analyze genetic variation and epigenetic modifications on native RNA and DNA molecules
Computational and Systems Biology Seminar Series 2023 - 24
Elucidating inter-species interactions in microbial communities using metabolic models
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator.
Machine Learning Reading Group @ CUED
Mean Field Theory of NN (postponed to March 2022)
Machine Learning Reading Group @ CUED
Representation Learning: A Causal Perspective
Computational and Systems Biology Seminar Series 2023 - 24
A multidimensional perspective on immune-mediated diseases: using genetic feature engineering to study shared risk factors in a reduced dimension space
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator.
Machine Learning Reading Group @ CUED
Ethics, Integrity and Good Practice in ML
MRC Biostatistics Unit Seminars
Virtual BSU seminar: "NanoSplicer: Accurate identification of splice junctions using Oxford Nanopore sequencing"
⚠️ This will be a online seminar. You can register for free at: https://www.eventbrite.co.uk/e/bsu-seminar-dr-heejung-shim-tickets-198278104147
Statistics
MARS via LASSO
Computational and Systems Biology Seminar Series 2023 - 24
Buffering genetic variation in populations
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator.
Machine Learning Reading Group @ CUED
Implicit Regularization in Deep Learning
MRC Biostatistics Unit Seminars
Virtual BSU Seminar: “Methodological Advances in Risk Prediction"
⚠️ This will be a virtual seminar. If you would like to attend, please email alison.quenault@mrc-bsu.cam.ac.uk for the joining information.
Computational and Systems Biology Seminar Series 2023 - 24
Computational Oncology at AstraZeneca
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator.
Machine Learning Reading Group @ CUED
Planning Meeting + PI Presentations
Statistics
Kernel Thinning and Stein Thinning
Computational and Systems Biology Seminar Series 2023 - 24
Understanding DNA Replication with Nanopore Sequencing, Deep Learning, and Mathematical Modelling
⚠️ Our intention is to deliver all Seminars in person, we will follow University Covid Guidance on this. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator.
Statistics
Global testing for dependent Bernoullis
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Artificial intelligence for prediction of genetic alterations directly from histology images
⚠️ Please email tania.smith@cruk.cam.ac.uk to request the Zoom registration link
Machine Learning Reading Group @ CUED
Towards Neuro-Causality: Relating Graph Neural Networks to Structural Causal Models
MRC Biostatistics Unit Seminars
BSU Virtual Seminar: “Estimating treatment effects from adaptive clinical trials”
⚠️ If you would like to join this virtual seminar, please email alison.quenault@mrc-bsu.cam.ac.uk for more information.
Machine Learning Reading Group @ CUED
CBL Alumni Talk - Task-specific routing of information in neural circuits via structured noise by Cristina Savin
Machine Learning Reading Group @ CUED
CBL Alumni Talk: Nonlinear filtering as a unifying principle in neuroscience by Jean-Pascal Pfister
Machine Learning Reading Group @ CUED
CBL Alumni Talk: Finale Doshi-Velez
Machine Learning Reading Group @ CUED
Pseudo-Points and State-Space Gaussian Processes
Machine Learning Reading Group @ CUED
CBL Alumni Talk: Latent Stochastic Differential Equations: An Unexplored Model Class.
Machine Learning Reading Group @ CUED
The Statistical Finite Element Method
MRC Biostatistics Unit Seminars
Virtual BSU Seminar: 'Confidence intervals for policy evaluation in adaptive experiments’
⚠️ If you would like to join this virtual seminar, please email alison.quenault@mrc-bsu.cam.ac.uk for more information.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Engineering model-based systems to monitor and steer subclonal dynamics
MRC Biostatistics Unit Seminars
Virtual Seminar: 'Probabilistic models of transcriptomic dysregulation in human genetic disease'
⚠️ If you would like to join this virtual seminar, please email alison.quenault@mrc-bsu.cam.ac.uk for more information.
Machine Learning Reading Group @ CUED
CBL Alumni Talk - Our Power as Technical Designers
Statistics
Correlated randomly growing graphs
MRC Biostatistics Unit Seminars
Virtual Seminar: 'Adapting Real-World Experimentation To Balance Enhancement of User Experiences with Statistically Robust Scientific Discovery'
⚠️ If you would like to join this virtual seminar, please email alison.quenault@mrc-bsu.cam.ac.uk for more information.
Machine Learning Reading Group @ CUED
Best of ICLR
Computational and Systems Biology
CCBI Annual Symposium 2021
Machine Learning Reading Group @ CUED
CBL Alumni Talk: Accurate Gaussian Processes and how they can help Deep Learning
MRC Biostatistics Unit Seminars
Virtual Seminar: 'Statistical Inference with M-Estimators on Bandit Data’
⚠️ If you would like to join this virtual seminar, please email alison.quenault@mrc-bsu.cam.ac.uk for more information.
Machine Learning Reading Group @ CUED
An Introduction to PAC-Bayes
Machine Learning Reading Group @ CUED
Automated Augmented Conjugate Inference for Gaussian Processes
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Determining the age of Barrett’s esophagus using stochastic multiscale modeling and epigenetic clocks
Machine Learning Reading Group @ CUED
CBL Alumni Talk: Examining Critiques in Bayesian Deep Learning
Machine Learning Reading Group @ CUED
Online Learning and Online Convex Optimisation
Machine Learning Reading Group @ CUED
Monte Carlo Gradient Estimation in Machine Learning
MRC Biostatistics Unit Seminars
Virtual Seminar: 'Bayesian pyramids: Identifying interpretable deep structure underlying high-dimensional data’
⚠️ If you would like to join this virtual seminar, please email alison.quenault@mrc-bsu.cam.ac.uk for more information.
Machine Learning Reading Group @ CUED
Secondmind's research activities to make Gaussian Processes industry proof
Machine Learning Reading Group @ CUED
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks
Machine Learning Reading Group @ CUED
Gaussian Processes I have Known
Machine Learning Reading Group @ CUED
Causal Representation Learning
Computational and Systems Biology
The genomes of transmissible cancers
Machine Learning Reading Group @ CUED
Long-Range Transformers
Statistics
Seminar Cancelled
Machine Learning Reading Group @ CUED
Inference in Stochastic Processes
MRC Biostatistics Unit Seminars
BSU Virtual Seminar: 'A Simulation-Free Approach To Assessing the Performance of the Continual Reassessment Method'
⚠️ If you would like to join this virtual seminar, please email alison.quenault@mrc-bsu.cam.ac.uk for more information.
Computational and Systems Biology
Regulation of gene expression and genome organisation
Machine Learning Reading Group @ CUED
Fairness in AI
Machine Learning Reading Group @ CUED
Variational Bayes as Surrogate Regression
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Visualizing Spatial Single-Cell Data with Vitessce
⚠️ Please email anna.toporska@cruk.cam.ac.uk by Friday 5th February to receive a ZOOM registration link
Computational and Systems Biology
Computational Biology in Drug Discovery
Computational and Systems Biology
Computational image analysis for coeliac disease diagnosis
Computational and Systems Biology
Bioinformatic analysis of T-cell antigen receptors as a novel diagnostic test for coeliac disease/ gluten sensitivity
Machine Learning Reading Group @ CUED
Bayesian optimization / Gaussian Process Bandits
Machine Learning Reading Group @ CUED
Meta-reinforcement learning
Machine Learning Reading Group @ CUED
Best of NeurIPS
MRC Biostatistics Unit Seminars
Virtual Seminar: ‘The DURATIONS design: a practical trial design to optimise treatment duration’
⚠️ If you would like to join this virtual seminar, please email: research_admin@mrc-bsu.cam.ac.uk for more information.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Deep learning in medical imaging - successes, pitfalls and challenges
⚠️ Please email anna.toporska@cruk.cam.ac.uk by Friday 11th December to receive a ZOOM registration link
MRC Biostatistics Unit Seminars
Virtual Seminar: 'PROGRESS in sample size calculations for clinical prediction model research'
⚠️ If you would like to join this virtual seminar, please email: research_admin@mrc-bsu.cam.ac.uk for more information.
Machine Learning Reading Group @ CUED
Neural Processes
Statistics
Generalized Kernel Two-Sample Tests
Computational and Systems Biology
AstraZeneca Oncology Bioinformatics case studies and the skill sets we value
Machine Learning Reading Group @ CUED
Large-scale sequential experimentation
MRC Biostatistics Unit Seminars
Virtual Seminar: ‘Score driven modeling of spatio-temporal data’
⚠️ If you would like to join this virtual seminar, please email: research_admin@mrc-bsu.cam.ac.uk for more information.
Computational and Systems Biology
Computational Morphodynamics - a quantitative description of multicellular development
Machine Learning Reading Group @ CUED
Symmetries in Reinforcement Learning
Computational and Systems Biology
Can machines understand the scientific literature?
Machine Learning Reading Group @ CUED
Gradient-based Hyperparameter Optimisation
MRC Biostatistics Unit Seminars
Virtual Seminar: 'Using auxiliary variables in mediation analysis to address unmeasured confounding'
⚠️ If you would like to join this virtual seminar, please email: research_admin@mrc-bsu.cam.ac.uk for more information.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Computational analysis of cancer genomes
⚠️ Please email anna.toporska@cruk.cam.ac.uk by Friday 6th November to receive a ZOOM registration link
Computational and Systems Biology
Computational Approaches to Drug Design and Computational Toxicology
Machine Learning Reading Group @ CUED
Best Papers from ICML 2020
Computational and Systems Biology
A multi-'omics graph convolutional network analysis for prediction of cancer survival
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Cancer Genetics Through the Lens of Mutational Signatures and the Two-Hit Hypothesis.
⚠️ Please email anna.toporska@cruk.cam.ac.uk by Friday 16th October to receive a ZOOM registration link
Computational and Systems Biology
Discovering the gene networks that regulate hunger
MRC Biostatistics Unit Seminars
Virtual BSU Seminar: 'Stochastic treatment interventions in causal survival analysis'
⚠️ If you would like to join this virtual seminar, please email alison.quenault@mrc-bsu.cam.ac.uk for more information.
Statistics
Title to be confirmed
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Characterizing and forecasting tumour evolution
⚠️ Please email anna.toporska@cruk.cam.ac.uk by Friday 25 September to receive a ZOOM registration link
MRC Biostatistics Unit Seminars
Virtual BSU Seminar: 'Assumption-lean inference for generalised linear model parameters'
⚠️ If you would like to join this virtual seminar, please email alison.quenault@mrc-bsu.cam.ac.uk for more information.
Machine Learning @ CUED
Efficient and Structured Uncertainty: Challenges and Opportunities
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Understanding regulatory systems and mechanisms of genetic interactions: from yeast to pediatric cancer
⚠️ Please email anna.toporska@cruk.cam.ac.uk to receive a ZOOM registration link
Machine Learning Reading Group @ CUED
Active Learning
Machine Learning Reading Group @ CUED
Recent advances in the theory and applications of VAEs
MRC Biostatistics Unit Seminars
Virtual BSU Seminar: 'Parameterizing Causal Marginal Models'
⚠️ If you would like to join this virtual seminar, please email: research_admin@mrc-bsu.cam.ac.uk for more information.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Statistical challenges posed by heterogeneous data from immunology and microbiology
⚠️ Please email anna.toporska@cruk.cam.ac.uk by Friday 12th June to receive a ZOOM registration link
Seminars on Quantitative Biology @ CRUK Cambridge Institute
“Focus on the Individual; The importance of chromosome-specific biology in generating aneuploidy patterns in cancer”
⚠️ Please email anna.toporska@cruk.cam.ac.uk to receive a ZOOM registration link
MRC Biostatistics Unit Seminars
Virtual Seminar: “Delayed-acceptance Sequential Monte Carlo”
⚠️ If you would like to join this virtual seminar, please email: research_admin@mrc-bsu.cam.ac.uk for more information.
Statistics
Neyman-Pearson Classification
Machine Learning Reading Group @ CUED
Best of ICLR 2020
Seminars on Quantitative Biology @ CRUK Cambridge Institute
CANCELLED
Machine Learning Reading Group @ CUED
Differentiable Planning
Machine Learning Reading Group @ CUED
Recent Developments in Bayesian Deep Learning
MRC Biostatistics Unit Seminars
Virtual Seminar: “Including expert knowledge in genomic selection through intuitive tree-based joint priors”
Machine Learning Reading Group @ CUED
Strategic Classification
Machine Learning Reading Group @ CUED
Machine Learning on Sets
Machine Learning Reading Group @ CUED
Boltzmann Generators and Stochastic Normalizing Flows
Seminars on Quantitative Biology @ CRUK Cambridge Institute
CANCELLED
Machine Learning Reading Group @ CUED
World Models
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Statistical challenges posed by heterogeneous data from immunology and microbiology- CANCELLED
Machine Learning Reading Group @ CUED
Federated Learning
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Visual Exploration of Longitudinal Oncology Data - CANCELLED
Statistics
Network change point detection
Machine Learning @ CUED
Game Playing Meets Game Theory: Strategic Learning from Simulated Play
MRC Biostatistics Unit Seminars
“Squeezing the most out of ridge”
Machine Learning Reading Group @ CUED
Self-Supervised Representation Learning
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Dissecting context dependent cancer signalling processes using CRISPR-based approaches
Machine Learning Reading Group @ CUED
Kernel Mean Embeddings
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Image-based quantitative morphology with geometrical models
Machine Learning Reading Group @ CUED
Neural Tangent Kernel
Machine Learning @ CUED
Robust Deep Learning Under Distribution Shift
Machine Learning Reading Group @ CUED
Scalable Gaussian Processes
Statistics
On the convergence of the Hamiltonian Monte Carlo algorithm and other irreversible MCMC methods
Machine Learning Reading Group @ CUED
Probabilistic Programming
Statistics
Optimal Transport for Machine Learning
Machine Learning Reading Group @ CUED
Neural Attention
Statistics
Multiscale Analysis of Bayesian CART
Machine Learning Reading Group @ CUED
Equivariance and Symmetries in CNNs
Machine Learning @ CUED
Models and inference for temporal Gaussian processes
Statistics
Identifying Cointegration by Eigenanalysis
Machine Learning Reading Group @ CUED
Hyperparameter Optimisation
Machine Learning Reading Group @ CUED
Meta-Learning or "Learning To Learn"
Machine Learning @ CUED
Reinforcement Learning at Huawei: Robustness, Safety, and Efficiency
Machine Learning @ CUED
Constructing temporal latent spaces: Representation learning for clustering and imputation on time series
Statistics
On Estimation of Unnormalized Density Models
Machine Learning @ CUED
Explaining Neural Networks: Post-hoc and Natural Language Explanations
Machine Learning Reading Group @ CUED
Hamiltonian Monte Carlo for Hierarchical Models
Statistics
Distributed Statistics à la Economics
Peter Whittle Lecture
Simplicity and Complexity of Belief-Propagation
Machine Learning @ CUED
Learning-Algorithms from Bayesian Principles
Machine Learning @ CUED
Rotation Invariant Householder Parameterization for Bayesian PCA
Machine Learning @ CUED
Two Approximate Sampling Methods for Bayesian Deep Learning
Machine Learning @ CUED
Semi-Unsupervised Learning with Deep Generative Models / Disentangling Improves VAEs' Robustness to Adversarial Attacks
Machine Learning @ CUED
Efficiency and Transferability of Neural Networks
Machine Learning @ CUED
Learning via Data Compression: Bayesian Coresets and Sparse Variational Inference
Machine Learning @ CUED
Deep Neural Networks: A Nonparametric Bayesian Approach with Local Competition
Machine Learning @ CUED
Information Consumption on Social Media: Efficiency, Trust, and Divisiveness
Statistics
Nonparametric maximum likelihood methods for binary response models with random coefficients
Statistics
Communication in the presence of sparsity
Statistics
MAP estimators and posterior consistency for Bayesian inverse problems with exponential priors
Statistics
On distributed Bayesian computation
Machine Learning @ CUED
Why Do We Need New Hardware & Software for Machine Intelligence?
Machine Learning Reading Group @ CUED
Particle MCMC
Computational and Systems Biology
CCBI Annual Symposium 2019
Machine Learning Reading Group @ CUED
Stochastic Differential Equations
Machine Learning @ CUED
Nonparametric Generative Modeling via Optimal Transport and Diffusions with Provable Guarantees
Machine Learning Reading Group @ CUED
Generalisation in neural networks
Statistics
Nuisance parameters
Machine Learning Reading Group @ CUED
An Overview of Normalizing Flows
MRC Biostatistics Unit Seminars
BSU Seminar: “Building Representative Matched Samples with Multi-valued Treatments in Large Observational Studies”
MRC Biostatistics Unit Seminars
BSU Seminar: "Information theory in dose-finding trials"
Machine Learning @ CUED
NeVAE: A Deep Generative Model for Molecular Graphs
Machine Learning @ CUED
Global model explainability via aggregation
Machine Learning Reading Group @ CUED
Sampling as Optimization
Machine Learning @ CUED
Robust machine learning for causal inference in health care
Seminars on Quantitative Biology @ CRUK Cambridge Institute
A systems biology approach to identify perturbed processes driving cancer
Computational Neuroscience
The K-FAC method for neural network optimization
Computational and Systems Biology
Towards the high-level sequence code of gene regulation
Machine Learning Reading Group @ CUED
Implicit Variational Inference
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Regulatory Genomics: From Basic Biology to Disease Mechanisms and Ageing
Statistics
Explicit stabilised Runge-Kutta methods and their application to Bayesian inverse problems
Computational and Systems Biology
Statistical Approaches to Personalised Medicine in Breast Cancer
Machine Learning Reading Group @ CUED
Continual Learning: Definitions, Benchmarks, and Approaches
Statistics
Analysis of Networks via the Sparse β-Model
Computational and Systems Biology
Chemical and Biological Data - from Compound Selection to Mode of Action Analysis (and Back Again)
Machine Learning Reading Group @ CUED
Causal Inference and Causal Reinforcement Learning
MRC Biostatistics Unit Seminars
BSU Seminar: “Optimal Feature Selection using model-based Deep Reinforcement Learning”
MRC Biostatistics Unit Seminars
BSU Seminar: “Sample size considerations for the design clinical trials – quantifying the target difference and the target no-difference”
Computational and Systems Biology
Ribosome profiling and virus infection
Machine Learning Reading Group @ CUED
Generative models for few-shot prediction tasks
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Learning Engines for Healthcare: Using Machine Learning to Transform Clinical Practice and Discovery
Machine Learning @ CUED
Online Meta-Learning
Computational and Systems Biology
Prioritization of mutations in coding and noncoding regions of the human genome using machine learning approaches
Machine Learning Reading Group @ CUED
Logical Uncertainty
Computational Neuroscience
High-dimensional dynamics of generalization error in neural networks: implications for experience replay
Machine Learning @ CUED
Gauge Equivariant Convolutional Networks on Manifolds
Computational and Systems Biology
Replacing pathologists with next generation diagnostics: use of artificial intelligence to analyse image and DNA sequencing data
MRC Biostatistics Unit Seminars
BSU Seminar: "Probabilistic approaches for optimal sequential feature acquisition"
Machine Learning Reading Group @ CUED
Stein Discrepancy
Machine Learning @ CUED
Observation and Intervention Incentives in Causal Influence Diagrams: Towards an Understanding of Powerful Machine Learning Systems
Computational and Systems Biology
Computational approaches to Immuno-Oncology drug development
MRC Biostatistics Unit Seminars
BSU Seminar: “How to obtain valid tests and confidence intervals for treatment effects after confounder selection”
Machine Learning @ CUED
Fairness for Sequential Decision Making Algorithms
Machine Learning @ CUED
Gaussian processes for inferring latent functions in complex data models
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Cell-of-origin of prostate cancer and clinical heterogeneity
MRC Biostatistics Unit Seminars
BSU Seminar: “Estimation in two-stage adaptive threshold enrichment clinical trials”
Computational and Systems Biology
Mathematics for mechanistic biology and drug discovery
Machine Learning Reading Group @ CUED
Neural Ordinary Differential Equations
Computational and Systems Biology
Mathematical modelling of rapid evolutionary processes
Machine Learning Reading Group @ CUED
Natural gradient in deep neural networks
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Non invasive detection of tissue specific cell death via methylation patterns of circulating DNA
Computational and Systems Biology
How space constrains evolution: lessons from bacteria and bacteriophage
Machine Learning Reading Group @ CUED
Graph Neural Networks
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Cancer Genome Evolution and Immune Escape
⚠️ You must email Anna.Toporska@cruk.cam.ac.uk prior to the talk if you are not based in CRUK CI and you wish to attend.
Statistics
Phase transitions on community detectability for various types of stochastic block models
MRC Biostatistics Unit Seminars
BSU Seminar: “Unsupervised substructure discovery in mass spectrometry metabolomics data”
Computational and Systems Biology
Discovering the gene networks that regulate hunger
Machine Learning Reading Group @ CUED
Defending Against Adversarial Attacks
Computational and Systems Biology
Personal Genomics
Machine Learning Reading Group @ CUED
Reinforcement Learning and Control as Probabilistic Inference
Computational and Systems Biology
Mapping the sub-cellular proteome
Computational and Systems Biology
Data-driven approaches to drug target identification
Machine Learning @ CUED
Causal Inference for Treatment Effects: A Theory and Associated Learning Algorithms
Peter Whittle Lecture
When Statistics Meets Computing
Computational and Systems Biology
Exploiting stochastic fluctuations to understand cellular processes and infer biochemical kinetics
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Exploring the role of ion channels in cancer using executable modelling
MRC Biostatistics Unit Seminars
BSU Seminar: “Statistical learning for drug screening in personalized cancer therapy”
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Gone fishing. Machine-learning guided discovery from public data.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Dynamics of HIV Intra-Patient Drug Resistance Evolution through Space and Time
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Patient-past based precision medicine: multi-morbidities in a life-course perspective
Machine Learning @ CUED
Interpretability - the myth, questions, and some answers
Machine Learning @ CUED
Constraint-based causal Discovery from NOnstationary/heterogeneous Data (CD-NOD)
MRC Biostatistics Unit Seminars
BSU Seminar: "Using Gaussian processes to model branching dynamics from single-cell data" (provisional)
Machine Learning @ CUED
Fast yet Simple Natural-Gradient Variational Inference in Complex Models
Machine Learning @ CUED
Variance in Policy Gradient methods and Learning Sequential Latent Variable Models
Machine Learning @ CUED
Structured deep models: Deep learning on graphs and beyond
MRC Biostatistics Unit Seminars
BSU Seminar: “Biomarker discovery through statistical signal processing and Bayesian modelling on large-scale quantitative proteomics data”
Machine Learning @ CUED
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
MRC Biostatistics Unit Seminars
BSU Seminar: "Mass spectrometry-based proteomics: challenges and opportunities"
Statistics
Title to be confirmed
MRC Biostatistics Unit Seminars
BSU Seminar: "Optimal bootstrapping with dependent data"
Machine Learning @ CUED
Semi-Generative Modelling: Domain Adaptation with Cause and Effect Features
Computational and Systems Biology
CCBI Annual Symposium
MRC Biostatistics Unit Seminars
BSU Seminar: “Cox-process representation and inference for stochastic reaction-diffusion processes”
Machine Learning @ CUED
Algorithmic Glass Ceiling in Social Networks
Statistics
Orbit recovery from invariants
MRC Biostatistics Unit Seminars
BSU Seminar: “Exchangeable Random Measures for Sparse and Modular Graphs with Overlapping Communities”
Machine Learning @ CUED
A Bayesian Perspective on Generalization and SGD
Machine Learning @ CUED
Algorithmic Glass Ceiling in Social Networks
MRC Biostatistics Unit Seminars
BSU Seminar: “Bayesian adaptive designs for Phase III trials”
Machine Learning Reading Group @ CUED
Neural Networks and Natural Language Processing
Machine Learning @ CUED
Structure in tensor-variate data: a trivial byproduct of simpler phenomena?
Statistics
On the gap between local recovery guarantees in structured compressed sensing and oracle estimates
Machine Learning Reading Group @ CUED
Information Theory, Codes, and Compression
Computational and Systems Biology
Ribosome profiling and virus infection
MRC Biostatistics Unit Seminars
BSU Seminar: “Quasi Markov Chain Monte Carlo Methods”
Machine Learning @ CUED
Lipschitz Global Optimization
Machine Learning Reading Group @ CUED
Statistical Learning Theory
Machine Learning Reading Group @ CUED
Deep Generative Models
Machine Learning Reading Group @ CUED
Minimum Description Length
Computational and Systems Biology
Multiple mouse reference genomes defines subspecies specific haplotypes and novel coding sequences
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Dissecting Receptor Tyrosine Kinase Signaling Networks by Quantitative Phosphoproteomics
Machine Learning Reading Group @ CUED
Machine Learning for Sounds
Machine Learning Reading Group @ CUED
NIPS 2017 Highlights
Machine Learning @ CUED
Variational inference for some models with Polya-Gamma latent variables and Gaussian process priors
Machine Learning @ CUED
Bayesian Generative Adversarial Networks
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Enhancers as regulatory hubs in mammalian embryogenesis and human congenital disease
⚠️ All people external to CRUK CI needs to be booked as visitors. Please contact Kamila at least 24 hours prior the talk.Thank you.
Machine Learning @ CUED
AI for Inclusive Finance
Machine Learning Reading Group @ CUED
Hardware Efficient Machine Learning
Computational and Systems Biology
Deciphering the origins of gene expression bursts at dawn, using computer-aided experimental design
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Inferring the Evolutionary History of Cancers: Statistical Methods and Applications
⚠️ All people external to CRUK CI needs to be booked as visitors. Thank you.
Machine Learning @ CUED
Backprop through the Void: Optimizing Control Variates for Black-Box Gradient Estimation.
Statistics
From linear programming to statistics: Fast algorithms for sampling based on interior point methods
Statistics
Optimal Sup-norm Rates and Uniform Inference on Nonlinear Functionals of Nonparametric IV Regression
Machine Learning @ CUED
Learning to Learn without Gradient Descent by Gradient Descent
Machine Learning Reading Group @ CUED
Learning to Learn
Computational and Systems Biology
Mapping the sub-cellular proteome
MRC Biostatistics Unit Seminars
Continuous inference for aggregated point process data
Statistics
Learning from MOM's principles
Machine Learning @ CUED
Towards true end-to-end learning & optimization
Machine Learning Reading Group @ CUED
WGAN and Optimal Transport
Computational and Systems Biology
Mathematical Modelling in Early Drug Discovery
Statistics
Accelerated Consensus via Min-Sum Splitting
Machine Learning Reading Group @ CUED
Interpretability in Machine Learning
Computational and Systems Biology
Systems approaches towards understanding temperature signalling in plants
Machine Learning Reading Group @ CUED
Deep Structured Prediction for Handwriting Recognition
Computational and Systems Biology
Evolution while you wait: population genetic modelling of rapid evolutionary processes
Machine Learning @ CUED
Targeted Disclosure to Support Auditing and Accountability for Automated Decision-making
MRC Biostatistics Unit Seminars
Individual dynamic predictions using landmarking and joint modelling: validation of estimators and robustness assessment
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Mutational heterogeneity in promoter regions in melanoma
⚠️ All external guests should arrive to the room at least 5 minutes before the start of the talk.
Machine Learning Reading Group @ CUED
Cooperative Inverse RL
Computational and Systems Biology
Data-driven approaches to drug target identification
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Improving Openness and Reproducibility of Scientific Research
⚠️ Please note that this event will be recorded. Guests should arrive to the Lecture Theatre at leat 5-10 minutes prior the talk, swich off their phones and minimise disruption and noise level to the minimum. Use of wi-fi is not allowed during the talk.
Machine Learning Reading Group @ CUED
Infer.NET
Machine Learning @ CUED
Nonlinear ICA using temporal structure: a principled framework for unsupervised deep learning
Computational and Systems Biology
Chemical and Biological Data - from Compound Selection to Mode of Action Analysis (and Back Again)
Machine Learning @ CUED
Transfer Learning for NLP
Computational and Systems Biology
Personal Genomics
MRC Biostatistics Unit Seminars
Extended multivariate generalised linear and non-linear mixed effect models
MRC Biostatistics Unit Seminars
Genome-wide epistasis in bacteria, new statistical tools and fresh biological insight
Machine Learning @ CUED
A Bayesian Treatment for Uncertainty -- and its application in health care
Seminars on Quantitative Biology @ CRUK Cambridge Institute
To be confirmed
⚠️ All people external to CRUK CI needs to be booked as visitors. Please contact Kamila at least 24 hours prior the talk.Thank you.
MRC Biostatistics Unit Seminars
Network Time Series
MRC Biostatistics Unit Seminars
A Bayesian model-based approach to finding cell-type level associations in heterogeneous methylation samples
Machine Learning @ CUED
Unbiased Estimation of the Eigenvalues of Large Implicit Matrices
MRC Biostatistics Unit Seminars
Dirichlet Process Mixtures of Multivariate Skew t-distributions for Unsupervised Clustering of Cell Populations from Flow-Cytometry Data
Machine Learning @ CUED
The Grammar Variational Autoencoder & Counterfactual Fairness
Machine Learning @ CUED
Accelerating computation of SVM and DNN by binary approximation
Machine Learning @ CUED
Towards User-Friendly Image Inpainting: Learning-to-Rank based Image Quality Assessment for Image Inpainting
Machine Learning @ CUED
Deep learning for autonomous driving
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Coding and non-coding cancer mutations
⚠️ All people external to CRUK CI needs to be booked as visitors. Please contact Kamila at least 24 hours prior the talk.Thank you.
Machine Learning @ CUED
Understanding Black-box Predictions via Influence Functions
Machine Learning @ CUED
A simple neural network module for relational reasoning
Machine Learning @ CUED
Future technology: machine learning using memristors networks
Machine Learning @ CUED
Future technology: machine learning using memristors networks
MRC Biostatistics Unit Seminars
“Joint variational inference for genetic association studies with multiple outcomes”
MRC Biostatistics Unit Seminars
“The xyz algorithm for fast interaction search in high-dimensional data”
Machine Learning @ CUED
On Different Distances Between Distributions and Generative Adversarial Networks
MRC Biostatistics Unit Seminars
“Identifying and evaluating personalised treatment recommendations”
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Statistical Bioinformatics at Scale
⚠️ All people external to CRUK CI needs to be booked as visitors. Please contact Kamila at least 24 hours prior the talk.Thank you.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
To be confirmed
⚠️ All people external to CRUK CI needs to be booked as visitors. Please contact Kamila at least 24 hours prior the talk.Thank you.
Statistics
Constrained low-rank matrix estimation
Statistics
The Bouncy Particle Sampler
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Building a bigger brain: genetic bases for the evolution of the human neocortex
⚠️ All people external to CRUK CI needs to be booked as visitors. Please contact Kamila at least 24 hours prior the talk.Thank you.
Machine Learning Study Group
Deep Learning Book - Meeting 9 - Representation Learning
Machine Learning Study Group
Deep Learning Book - Meeting 8 - Autoencoders
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Functional variation in the human genome: lessons from the transcriptome
⚠️ If you have a question about this talk or would like to attend this talk but you are from outside CRUK CI, please contact Kamila.Lembrych-Turek. Please note that all external visitors have to be booked onto an internal visitors' booking system.
MRC Biostatistics Unit Seminars
"The Analysis of Recurrent Events: A Summary of Methodology and Informative Censoring Considerations"
Machine Learning Study Group
Deep Learning Book - Meeting 7 - Neural Turing Machines & Conditional Random Fields as RNNs
Machine Learning Reading Group @ CUED
Kernel Mean Embeddings
Information Engineering Division seminar list
Bayesian Optimization for Probabilistic Programs
Machine Learning Study Group
Deep Learning Book - Meeting 6 - Recurrent Neural Networks
Machine Learning @ CUED
Differentially Private Bayesian Learning
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Alternative splicing: widespread fine-tuning regulatory process or costly errors?
⚠️ All external to CRUK CI people need to be booked at least 24 hours prior the talk. Please contact Kamila by email if you would like to come.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Alternative splicing: widespread fine-tuning regulatory process or costly errors?
⚠️ All external to CRUK CI people need to be booked at least 24 hours prior the talk. Please contact Kamila by email if you would like to come.
Computational and Biological Learning Seminar Series
Control, inference and learning
Machine Learning Reading Group @ CUED
Differential Privacy
Machine Learning @ CUED
Differential Privacy Tutorial
Machine Learning Study Group
Deep Learning Book - Meeting 5 - ResNets and DenseNets
Computational and Systems Biology
Two transmissible cancers in Tasmanian devils
Machine Learning @ CUED
Cooperative Inverse Reinforcement Learning
MRC Biostatistics Unit Seminars
CANCELLED - Identifying and evaluating personalised treatment recommendations
Machine Learning Study Group
Deep Learning Book - Meeting 4 - Convolutional Networks
Statistics
High frequency statistics of semimartingales
Machine Learning Reading Group @ CUED
Probabilistic Numerics
Computational and Systems Biology
Integrating Chemical and Biological Data for Drug Discovery
Machine Learning Study Group
Deep Learning Book - Meeting 3 - Optimization
Machine Learning @ CUED
Bayesian optimisation in many dimensions with bespoke probabilistic programs
Computational and Systems Biology
Computational Biology and Drug Discovery
Machine Learning Study Group
Deep Learning Book - Meeting 2 - Regularization
Statistics
Sleeping Beauty’s Credences
Computational and Systems Biology
Ribosome profiling and virus infection
Machine Learning Study Group
Deep Learning Book - Meeting 1 - Deep Feedforward NNs
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The blind watch-breaker: evolution at regulatory sites in cancer
⚠️ If you have a question about this talk or would like to attend this talk but you are from outside CRUK CI, please contact Kamila.Lembrych-Turek. Please note that all external visitors have to be booked onto an internal visitors' booking system.
Machine Learning @ CUED
Variational Bayes In Private Settings
Machine Learning @ CUED
Julia: Introduction and new developments
Statistics
High-Dimensional Bayesian Geostatistics
MRC Biostatistics Unit Seminars
"Dynamic prediction of survival using landmarking in large healthcare databases, with an application in cystic fibrosis"
Machine Learning Reading Group @ CUED
NIPS 2016 papers in 5mins
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Modeling cancer evolution from genomic data
⚠️ Please note that all external visitors have to be booked onto an internal visitors' booking system.
MRC Biostatistics Unit Seminars
“Statistical opportunities and challenges in observational health data: Addressing missingness using two-phase sampling for nonresponse: methods and benefits"
Machine Learning @ CUED
Bayesian optimality and frequentist extended admissibility are equivalent in saturated models
Machine Learning @ CUED
Hierarchical Multi-Agent Reinforcement Learning through Communicative Actions for Human-Robot Collaboration
MRC Biostatistics Unit Seminars
Provisional title: "Percentage study weights in meta-analysis and meta-regression"
Machine Learning @ CUED
Variational autoencoders with latent graphical models
Statistics
Gaussian vectors, half-spaces, and convexity
Machine Learning Reading Group @ CUED
Symmetry in Statistical Models
Machine Learning @ CUED
Learning with limited supervision
MRC Biostatistics Unit Seminars
"A Bayesian analysis of microbiome data"
Statistics
Measuring sample quality with diffusions
Machine Learning Reading Group @ CUED
Bayesian Optimization
Machine Learning @ CUED
A tale of P-matrices and TripleSpinners - the unreasonable effectiveness of structured models in nonlinear embeddings
Computational and Systems Biology
Mining scientific diagrams for semantic information
Machine Learning @ CUED
Rejection Sampling Variational Inference
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Title to be confirmed
⚠️ If you have a question about this talk or would like to attend this talk but you are from outside CRUK CI, please contact Kamila.Lembrych-Turek. Please note that all external visitors have to be booked onto an internal visitors' booking system.
Machine Learning Reading Group @ CUED
deep generative models
Machine Learning @ CUED
Probabilistic Numerical Computation: A New Concept?
Computational and Systems Biology
Mapping the sub-cellular proteome
Computational and Systems Biology
Mapping the sub-cellular proteome
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Transposable elements and epigenome evolution
⚠️ If you have a question about this talk or would like to attend this talk but you are from outside CRUK CI, please contact Kamila.Lembrych-Turek. Please note that all external visitors have to be booked onto an internal visitors' booking system.
Statistics
Short Course: Lecture 2 - Sample Covariance Operators: Normal Approximation and Concentration
Machine Learning Reading Group @ CUED
Sketching methods
Statistics
Short Course: Lecture 1 - Sample Covariance Operators: Normal Approximation and Concentration
MRC Biostatistics Unit Seminars
"Breaking non-identifiability using genetic information : an application to metabolite data and gene expression"
Machine Learning @ CUED
A talk in two parts: (1) AI Neuroscience: How much do deep neural networks understand about the images they classify? (2) Robots that can adapt like animals.
⚠️ Note venue: James Dyson Building
Machine Learning Reading Group @ CUED
A crash-course on Bayesian Reinforcement Learning
Machine Learning @ CUED
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models
Computational and Systems Biology
Genome architecture and chromatin regulation in C. elegans
Machine Learning @ CUED
Robots learning on the move: deep learning from lots of demonstration
Machine Learning @ CUED
Probabilistic modeling for position and orientation estimation using inertial sensors
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Evolution, genomics and mode of action of long noncoding RNAs in mammalian cells
⚠️ If you have a question about this talk, please contact Kamila.Lembrych-Turek from CRUK CI.
Computational and Systems Biology
Transcriptional and phenotypic variability in response to temperature in plants
MRC Biostatistics Unit Seminars
"The Analysis of Recurrent Events: A Summary of Methodology and Informative Censoring Considerations"
Computational and Systems Biology
Using evolutionary sequence variation to build predictive models of protein structure and function.
Machine Learning @ CUED
Moment matching for latent variable models: from ICA to LDA and CCA
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The Long-legged mouse and the Impossible Hybrid – the genetics of genome evolution in the mouse from stem cells to whole organisms
⚠️ If you have a question about this talk, please contact Kamila.Lembrych-Turek.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Non-coding genome function in pancreatic islets and diabetes
⚠️ If you have a question about this talk, please contact Kamila.Lembrych-Turek.
MRC Biostatistics Unit Seminars
Title TBC
Machine Learning @ CUED
Multiresolution Matrix Factorization
Machine Learning @ CUED
Dynamic Models for Health Data
MRC Biostatistics Unit Seminars
"Addressing missingness using two-phase sampling for nonresponse: methods and benefits"
Machine Learning @ CUED
Learning with Memory Embeddings
Machine Learning @ CUED
Data Driven Discrete Time Modeling of Continuous Time Nonlinear Systems: Problems, Challenges, Success Stories
Seminars on Quantitative Biology @ CRUK Cambridge Institute
A Bayesian ordination method for 16S microbiome profiling data
Machine Learning @ CUED
Inference as Learning
Machine Learning @ CUED
Interpretable and interactive machine learning
Machine Learning @ CUED
Discriminative Embeddings of Latent Variable Models for Structured Data
Machine Learning @ CUED
Structured Dynamic Graphical Models & Scaling Multivariate Time Series Methodology
Machine Learning @ CUED
Scaling and Generalizing Approximate Bayesian Inference
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Decision making in hierarchical multi-label classification (HMC) problems
MRC Biostatistics Unit Seminars
"A non-stationary Bayesian model for across-site heterogeneity in molecular phylogenetics"
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Title to be confirmed
arg58's list
A modular architecture for Unicode text compression
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Sex chromosomes in development and disease
Statistics
Chaining and convexity
Machine Learning @ CUED
Modeling the Dynamics of Online Learning Activity
MRC Biostatistics Unit Seminars
"Exploring dependence between categorical variables: Benefits and limitations of using variable selection within Bayesian clustering in relation to searching for interactions"
Machine Learning @ CUED
Developments in Exact Inference in Graphical Models
Machine Learning @ CUED
Approximation strategies for structure learning in Bayesian networks
⚠️ Note: via Skype!
Machine Learning @ CUED
Automated Reasoning and AI for Large Formal Mathematics
Machine Learning Reading Group @ CUED
Partially Observable Markov Decision Processes (POMDPs)
Machine Learning @ CUED
Variational inference for scalable Gaussian process approximations
Machine Learning @ CUED
Novel MCMC and SMC schemes for Poisson-Kingman Bayesian Nonparametric mixture models
Machine Learning @ CUED
Turing: Rejuvenating Probabilistic Programming in Julia
Machine Learning @ CUED
Towards Weaker Supervision and Simpler Pipelines in Speech Recognition
Machine Learning Reading Group @ CUED
Learning polynomials with Neural Networks
MRC Biostatistics Unit Seminars
"Modelling the evolution of brain signals"
Machine Learning @ CUED
Sum-Product Networks for Probabilistic Modeling
Peter Whittle Lecture
Dimers Day in Cambridge
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Gene-drug interaction screens in cancer
Machine Learning @ CUED
MLE-Struct: Bethe Learning of Graphical Models
MRC Biostatistics Unit Seminars
"Improved ranking and selection for large-scale inference"
Machine Learning Reading Group @ CUED
An introduction to Bayesian nonparametrics: some inference schemes for infinite mixture models
MRC Biostatistics Unit Seminars
"The analysis of variance and the analysis of causes"
Machine Learning Reading Group @ CUED
Topics in Expectation Propagation
MRC Biostatistics Unit Seminars
"Some aspects in high-dimensional Bayesian model choice"
Machine Learning Reading Group @ CUED
Deep Q-Learning and AlphaGo
Machine Learning Reading Group @ CUED
inference failures in probabilistic programming
Cambridge Area Sequencing Informatics Meeting VIII (2016)
CASIM VIII: KEYNOTE SPEAKER - Ebola to Zika: portable nanopore sequencing for outbreak surveillance
Cambridge Area Sequencing Informatics Meeting VIII (2016)
CASIM VIII: DISCUSSION 4 - Analysis of cancer genomes
Cambridge Area Sequencing Informatics Meeting VIII (2016)
CASIM VIII: DISCUSSION 3 - Hot topics in transcriptomics
Cambridge Area Sequencing Informatics Meeting VIII (2016)
CASIM VIII: RISING STARS TALKS - A landscape of pharmacogenomics interactions in cancer
Cambridge Area Sequencing Informatics Meeting VIII (2016)
CASIM VIII: RISING STARS TALKS - Emergence and progression of naive pluripotency in mammalian embryogenesis
Cambridge Area Sequencing Informatics Meeting VIII (2016)
CASIM VIII: DISCUSSION 2: 3D genomics
Cambridge Area Sequencing Informatics Meeting VIII (2016)
CASIM VIII: DISCUSSION 1 - Buggy science: improving bioinformatics software quality
Cambridge Area Sequencing Informatics Meeting VIII (2016)
CASIM VIII: Reproducibility Workshop follow up
Machine Learning Reading Group @ CUED
Variational Methods and Compressed Sensing
Machine Learning @ CUED
Inference and Learning in the Anglican Probabilistic Programming System
Machine Learning Reading Group @ CUED
Fast Fusion of Multi-band Images: A Powerful Tool for Super-resolution
MRC Biostatistics Unit Seminars
"Better prediction by use of co-data: Adaptive group-regularized ridge regression"
Machine Learning @ CUED
Unsupervised Risk Estimation with only Structural Assumptions
Computational Neuroscience
It's the Network Dummy: Exhuming the reticular theory while shoveling a little dirt on the neuron doctrine
Machine Learning @ CUED
The geometry of uncertainty
Statistics
Information bounds for inverse problems with application to deconvolution and Lévy models
Machine Learning Reading Group @ CUED
Probabilistic programming
Computational and Systems Biology
Using C. elegans to learn principles of eukaryotic chromatin regulation
MRC Biostatistics Unit Seminars
"Design for ABC and history matching with Gaussian processes"
Machine Learning Reading Group @ CUED
Learning by learning rich generative models
Computational and Systems Biology
Circulating tumour cells: a model from breast cancer to bone metastasis
MRC Biostatistics Unit Seminars
"The Implications of Differential Clustering for the Analysis of Binary Outcome Measures"
Machine Learning @ CUED
A more Automated Statistician
Machine Learning Reading Group @ CUED
Natural gradient descent and variational inference
Computational and Systems Biology
Clonally transmissible cancers in dogs and Tasmanian devils
Computational and Systems Biology
Title to be confirmed
Machine Learning Reading Group @ CUED
Differentiable Data Structures and (if we have time) POMDPs
⚠️ NOTE Topic Change
Computational and Systems Biology
Comparative genomics of RNA viruses
MRC Biostatistics Unit Seminars
"Understanding the role of secondary outcomes in multivariate meta-analysis"
Computational and Systems Biology
Cellular Systems Biology of Chromosome Dynamics
MRC Biostatistics Unit Seminars
"Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models"
Machine Learning Reading Group @ CUED
Random projection ensemble classification
Computational and Systems Biology
Mining scientific diagrams for semantic information
Machine Learning Reading Group @ CUED
Deep learning for time series
Computational and Systems Biology
Understanding tumour heterogeneity in glioblastoma
Machine Learning Reading Group @ CUED
Stochastic discrete integration
Computational and Systems Biology
Defining cell states and regulatory networks by single cell expression profiling
MRC Biostatistics Unit Seminars
"An Unbiased and Scalable Monte Carlo Method for Bayesian Inference for Big Data"
Machine Learning @ CUED
General Reinforcement Learning
Statistics
Boosting in the presence of outliers: adaptive classification with non-convex loss functions
MRC Biostatistics Unit Seminars
"Blood-based biomarkers of Alzheimer's disease & Temporal Clustering of biological, medical and wearable data"
Computational and Systems Biology
Integrating Chemical and Biological Data for Drug Discovery
Machine Learning Reading Group @ CUED
Stochastic optimization and adaptive learning rates
Statistics
Fast low-rank estimation by projected gradient descent: Statistical and algorithmic guarantees
Machine Learning Reading Group @ CUED
Logic, Theorem Proving, and Probabilistic Programming
Computational and Systems Biology
Defining Transcription factor specificity and redundancy in Drosophila
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Adventures in structural variation and evolution in cancer
Machine Learning Reading Group @ CUED
Connections between kernels, GPs, and NNs
Computational and Systems Biology
Systems approaches towards understanding temperature signalling in plants
Machine Learning @ CUED
Inference of a partially observed kinetic Ising model
Machine Learning Reading Group @ CUED
Detecting paraphrases using recursive autoencoders
Computational and Systems Biology
Spatio-temporal organization of replication: On genome evolution and large-scale chromatin folding
MRC Biostatistics Unit Seminars
Title TBC
Machine Learning Reading Group @ CUED
Bayesian optimization and its applications
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Mining the root causes, driver mutations snd therapeutic opportunities from recalcitrant cancers
Computational and Systems Biology
Decoding 3-D vision in the human brain
Machine Learning Reading Group @ CUED
LP relaxations for MAP inference
Computational and Systems Biology
Bioinformatics to support cancer therapeutics
Statistics
Nonstandard complete class theorems
Machine Learning @ CUED
Meta-Bayesian Analysis
Computational and Systems Biology
Mapping the sub-cellular proteome
Machine Learning @ CUED
Efficient Inference and Learning with Intractable Posteriors? Yes, Please.
Machine Learning @ CUED
Efficient multi-task Gaussian process models for genome-wide association studies
Machine Learning @ CUED
Harmonic Exponential Families and Group-Equivariant Convolution Networks
Machine Learning @ CUED
Higher Order Fused Regularization for Supervised Learning with Grouped Parameters
Machine Learning @ CUED
A-Star Sampling Review
Machine Learning @ CUED
Convex Factorization Machines
Machine Learning @ CUED
Belief and Truth in Hypothesised Behaviours
Machine Learning @ CUED
Training and Understanding Deep Neural Networks for Robotics, Design, and Perception
Machine Learning @ CUED
Information-Theoretic Bounded Rationality
Machine Learning @ CUED
The limits of MAP inference by MWSS on perfect graphs
Machine Learning @ CUED
Scalable Gaussian Processes for Scientific Discovery
Machine Learning @ CUED
MCMC for non-linear state space models using ensembles of latent sequences
⚠️ (via Skype!)
Machine Learning @ CUED
Gradient-based hyperparameter optimization through reversible learning
Machine Learning @ CUED
Rich Component Analysis
Machine Learning @ CUED
A new MCMC hybrid scheme for Poisson-Kingman Bayesian Nonparametric mixture models
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Discovering enhancer sequences with a role in vertebrate left-right patterning
Seminars on Quantitative Biology @ CRUK Cambridge Institute
A Horizontal Transfer from Bacteria to Fungi Enhances Fungal Pathogenicity
Machine Learning @ CUED
Extreme Classification: A New Paradigm for Ranking & Recommendation
Machine Learning @ CUED
Convex and non-convex worlds in machine learning
Machine Learning @ CUED
Random Function Classes for Machine Learning
Machine Learning @ CUED
Explaining Non-Linear Classifier Decisions with application to Deep Learning
Machine Learning @ CUED
Deep Gaussian processes and variational propagation of uncertainty
Machine Learning @ CUED
Deep Learning
Machine Learning @ CUED
Random Function Classes for Machine Learning
Machine Learning @ CUED
Unsupervised Learning with Latent Variable Models
Machine Learning @ CUED
Unsupervised Learning with Latent Variable Models
Machine Learning @ CUED
Structural Markov laws / Geometry and HMC
Machine Learning @ CUED
Mean Field Approaches to Two Sequential Decision Making Problems.
⚠️ This talk will be given via Skype
Machine Learning @ CUED
Do Deep Nets Really Need to be Deep?
Statistics
Analysis of complex phenotypes in genomics
Machine Learning Reading Group @ CUED
Convolutional Neural Networks
Computational and Systems Biology
Tenth Annual Symposium of the Cambridge Computational Biology Institute
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Title to be confirmed
Statistics
Text Mining in Dynamic Networks of Documents
Machine Learning Reading Group @ CUED
Hessian-free Optimisation for Neural Networks
Machine Learning @ CUED
Probabilistic numerics: treating numerical computation as learning, or; it's Bayes all the way down
Machine Learning Reading Group @ CUED
Scalable MCMC
Statistics
Robust Matrix Completion
Machine Learning @ CUED
Machine Learning for Quantitative Finance: A collaboration between the Cambridge Machine Learning Group and Cambridge Capital Management
Machine Learning Reading Group @ CUED
Causal Inference
Machine Learning @ CUED
Title to be confirmed
Machine Learning Reading Group @ CUED
Gaussian Process Models for Time Series
Machine Learning @ CUED
Inference for infinite mixture models and Gaussian Process mixtures of experts using simple approximate MAP Inference
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Reconstructing the evolutionary history of tumours
Statistics
Stable Weights that Balance Covariates for Causal Inference and Estimation with Incomplete Outcome Data
⚠️ Note the different room
Machine Learning Reading Group @ CUED
Informational Geometry
Machine Learning Reading Group @ CUED
Deep Gaussian Processes
Machine Learning Reading Group @ CUED
Combinatorial Stochastic Processes in Bayesian Nonparametrics
Machine Learning @ CUED
Evolutionary dynamics in a continuous public goods game
Machine Learning @ CUED
An introduction to the Mondrian Process
Computational and Systems Biology
Decoding 3-D vision in the human brain
Computational and Systems Biology
Clonally transmissible cancers in dogs and Tasmanian devils
Machine Learning @ CUED
Population Inference for Functional Brain Connectivity
Microsoft Research Machine Learning and Perception Seminars
Workshop: Machine Learning in Cambridge 2015
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Probabilistic approaches to understanding bird conversations
Computational and Systems Biology
Transcriptional Network Control of Blood Cell Development
Machine Learning @ CUED
A* Sampling
Computational and Systems Biology
Towards a molecular psychophysics of decision making in neuro-development and repair
Statistics
Some ideas in nonparametric estimation
Machine Learning Reading Group @ CUED
Variance Reduction Techniques and Stochastic Optimisation for Monte Carlo
Computational and Systems Biology
Image analysis tools for cancer biology: how could we make it better?
Machine Learning @ CUED
Orthologous networks in biological systems
Computational and Systems Biology
MPhil in Computational Biology Open Day
Computational and Systems Biology
Genomics of transcription factor redundancy
Statistics
A novel (pre-)metric for causal graphs
Machine Learning Reading Group @ CUED
Transfer Learning
Machine Learning @ CUED
Latent Branching Trees
Peter Whittle Lecture
An afternoon of talks exploring the links between classical information theory, probability, statistics and their quantum counterparts.
Computational and Systems Biology
Mathematical Image Analysis for Cancer Research
Machine Learning @ CUED
Experiments with Non-parametric Topic Models
Machine Learning Reading Group @ CUED
Advanced HMC
Computational and Systems Biology
There is no medicine except in the light of models
Machine Learning Reading Group @ CUED
Active Learning
Machine Learning @ CUED
The Blended Paradigm: A Bayesian Approach to Handling Outliers and Misspecified Models
Machine Learning Reading Group @ CUED
Deep Probabilistic Models (Wake/Sleep)
Computational and Systems Biology
Simulation Approaches to Biomolecular Recognition and Assembly
Statistics
Dynamic functional principal components
Machine Learning @ CUED
Machine Translation with LSTMs
⚠️ Room changed to LR3B in Inglis building and time changed to 10:30
Machine Learning Reading Group @ CUED
PAC Bayes
Computational and Systems Biology
Multi-scale studies on transcription factors
Machine Learning @ CUED
Oracle Variational Inference
Collaborative research: funding available for collaborative research out of Science and Technology Funding Council areas.
STFC collaborative R&D funding
⚠️ Free parking on Clerk Maxwell Road (2 minutes from the Cavendish). Parking closer very limited, please email organiser if needed.
Machine Learning Reading Group @ CUED
LSTM and Recurrent Neural Networks
Computational and Systems Biology
Biological Databases: More than just stamp collections.
Machine Learning @ CUED
Bayesian modeling for high-level real nursing activity recognition using accelerometers
⚠️ short talk
Machine Learning Reading Group @ CUED
Automatic Differentiation with Theano
Computational and Systems Biology
Using human genome variation to study history and cellular function
Machine Learning Reading Group @ CUED
State Space Abstraction for Reinforcement Learning
Computational and Systems Biology
High-content microscopy: big-data biology goes spatio-temporal
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Whole-genome sequencing of cell-free DNA in maternal plasma
Machine Learning Reading Group @ CUED
Kernel Embedding for Distributions
Computational and Systems Biology
Computational analyses of high-throughput spatial proteomics data
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Targeting the brain tumour stem cell phenotype with small molecules
Statistics
Adaptive posterior contraction
Machine Learning @ CUED
A Tutorial on Probabilistic Programming
Computational and Systems Biology
Population genetic models of evolution
CUED Control Group Seminars
Optimal control and optimal sampling: A statistical physics perspective.
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Dissecting translation efficiency through lab evolution, genome engineering and inspection of the cancerous genome
Computational and Systems Biology
Systems approaches towards understanding temperature signalling in plants
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Modelling the transcriptional response to ER signalling in breast cancer cells
Peter Whittle Lecture
Peter Whittle Colloquium
Cambridge Area Sequencing Informatics Meeting VI (2014)
CASIM VI: Keynote Address - Using Hi-C to Determine 3-D Structures of Whole Genomes in Single Cells
Cambridge Area Sequencing Informatics Meeting VI (2014)
CASIM VI: Rising stars 2 - Sequencing Applications in Health and Disease
Cambridge Area Sequencing Informatics Meeting VI (2014)
CASIM VI: Discussion 3 - Single Cell Sequencing
Cambridge Area Sequencing Informatics Meeting VI (2014)
CASIM VI: Rising stars 1 - Data Analysis and Data Sharing Methods
Cambridge Area Sequencing Informatics Meeting VI (2014)
CASIM VI: Discussion 2 - Long Read / New Technologies
Cambridge Area Sequencing Informatics Meeting VI (2014)
CASIM VI: Discussion 1 - Local Computational Resources and Issues
Machine Learning @ CUED
New Methods in Bayesian Optimization for Machine Learning
Machine Learning @ CUED
A marginal sampler for σ-Stable Poisson-Kingman mixture models
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Discovery and allele frequency estimation of somatic twilight zone insertions and deletions
Machine Learning @ CUED
Local Deep Kernel Learning for Efficient Non-linear SVM Prediction
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Therapeutic landscape of cancer drivers
Microsoft Research Machine Learning and Perception Seminars
Local Deep Kernel Learning for Efficient Non-linear SVM Prediction
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Unsupervised Many-to-many Object Matching
Machine Learning @ CUED
Probabilistic Numerics - a snapshot of an emerging community
Machine Learning @ CUED
On the Bethe approximation
Machine Learning @ CUED
Gaussian process regression on graphs
Machine Learning @ CUED
Implicit Representation Networks
Machine Learning @ CUED
Scalable Deep Gaussian Processes
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The Cancer Genome Atlas: oncogenic signature classes and the design of combinatorial therapy
Machine Learning Reading Group @ CUED
Unsupervised Representation Learning
Machine Learning @ CUED
Active Learning of Linear Embeddings for Gaussian Processes
Machine Learning @ CUED
Bayesian monitoring for the Comprehensive Nuclear-Test-Ban Treaty
Machine Learning @ CUED
Unifying logic and probability: A "New Dawn" for Artificial Intelligence?
⚠️ NOTE THE SPECIAL VENUE (Microsoft Research)
Machine Learning Reading Group @ CUED
Time-varying dynamic Bayesian network reconstruction with information sharing
Machine Learning Reading Group @ CUED
Advanced Gaussian Process approximation methods
Machine Learning @ CUED
Practical Machine Learning at Facebook. Examples and Lessons Learnt.
⚠️ Room changed to LR4
Machine Learning @ CUED
Bayesian inference for integer-valued Lévy processes with Non-Gaussian Ornstein-Uhlenbeck volatility modelling
⚠️ short talk (30 mins) - NOTE TIME CHANGE
Machine Learning Reading Group @ CUED
Statistical model criticism
Machine Learning @ CUED
Density Estimation in Infinite Dimensional Exponential Families
Machine Learning @ CUED
Stable Poisson-Kingman species sampling priors generated by general ordered size biased generalized gamma mixing distributions
Statistics
It is hard to be strongly faithful
Machine Learning Reading Group @ CUED
Functional Programming
Machine Learning Reading Group @ CUED
The Bernoulli Factory problem and some connections with Computable Analysis
Machine Learning Reading Group @ CUED
Neural Network Language Modelling
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Variations in genetic and phenotypic diversity during breast cancer progression.
Machine Learning @ CUED
Probabilistic computing applications: BayesDB and stochastic digital circuits
Machine Learning Reading Group @ CUED
Loopy belief propagation
Machine Learning @ CUED
Probabilistic computing for Bayesian inference
Machine Learning @ CUED
Machine Learning and Order Book Dynamics
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Single molecule approaches for studying gene expression in intact mammalian tissues.
Machine Learning @ CUED
Policy Evaluation with Temporal Differences
Machine Learning @ CUED
Matrix Means, Distances, Kernels, and Geometric Optimization
Machine Learning @ CUED
Learning to Learn for Structured Sparsity
Machine Learning @ CUED
Bayesian nonparametric dynamic-clustering and genetic imputation
Statistics
Invariant Coordinate Selection revisited: Fisher Symmetry and Symmetric Component Analysis
Machine Learning @ CUED
Parameter estimation in deep learning architectures: Two new insights.
⚠️ Note: time is 12 noon (*not* 11am)
Machine Learning @ CUED
Bayesian canonical correlation analysis
Machine Learning @ CUED
Cambridge - Tuebingen PhD Applicant Talks (via Skype)
⚠️ Interview talks via Skype
Machine Learning @ CUED
Generative probabilistic programming: applications and new ideas
Statistics
The Double Sin of the Skew-Normal: Skew-Symmetric Families of Distributions and Fisher Information
Machine Learning @ CUED
Bayesian nonparametrics: Dependency and Constraint Modeling
⚠️ Note: TALK via Skype!
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The Resistant Cancer Cell Line (RCCL) collection – cancer cell lines with acquired drug resistance as a pre-clinical and basic science model
Machine Learning @ CUED
Bayesian Nonparametric Model for Power Disaggregation
Machine Learning @ CUED
Probabilistic machine learning for knowledge extraction from videos and text
⚠️ Note venue: LR6
Machine Learning Reading Group @ CUED
An introduction to Sequential Monte Carlo
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Using time-resolved genetic data to study the evolution of drug resistance.
Machine Learning @ CUED
Frequentist coverage of adaptive nonparametric Bayesian credible sets
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Profiling the Subclonal Copy Number Architecture from Whole Genome Sequencing of Heterogeneous Tumours
Machine Learning Reading Group @ CUED
Probabilistic Data Structures and Algorithms
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Systems biology of stem cell fate
Statistics
Sharp bounds for compressive learning
Machine Learning Reading Group @ CUED
Information Theory and Method of Types: Channels, Quantizers, and Divergences
Machine Learning @ CUED
Anglican; Particle MCMC inference for Probabilistic Programs
Machine Learning @ CUED
Sparse discriminative latent characteristics for predicting cancer drug sensitivity
Microsoft Research Machine Learning and Perception Seminars
Bayesian Machine Learning for Controlling Autonomous Systems
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Statistics
High Dimensional Influence Measure
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Incorporating Prior Biological Knowledge into Genetic Association Studies
Statistics
Regret-regression for optimal dynamic treatment allocation, without and with missing data
Machine Learning Reading Group @ CUED
Integrated Nested Laplace Approximation (INLA)
Statistics
High-dimensional causal inference
Machine Learning Reading Group @ CUED
Spectral Learning
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Measuring within-tumour diversity as a universal biomarker for cancer prognosis
Machine Learning Reading Group @ CUED
Random Projections
Computational and Systems Biology
Physical constraints can encode bacterial promoter regulatory logic
Machine Learning @ CUED
Contrastive Learning Using Spectral Methods
Machine Learning Reading Group @ CUED
Herding: Driving Deterministic Dynamics To Learn And Sample Probabilistic Models
Statistics
Matching Quantiles Estimation
Machine Learning Reading Group @ CUED
Bayesian and Bandit Optimization
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Analysis of a large cancer gene screen in myelodysplastic syndromes
Statistics
Implementing (Multiple) Monte Carlo Tests
Statistics
The Geometry of Needlets Excursion Sets
Machine Learning @ CUED
Nonparametric Bayesian statistics with exchangeable random structures
Machine Learning @ CUED
Dissecting genotype to phenotype relationships
Microsoft Research Machine Learning and Perception Seminars
Compositionality in Vision and Language
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
CANCELLED: Local Deep Kernel Learning for Efficient Non-linear SVM Prediction
⚠️ CANCELLED
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Colon CSCs are sensitized by HDACinhibitors in a FOXO-dependent fashion
Machine Learning @ CUED
Clustering Based on Predictive Variances in Gaussian Process Regression Models
Microsoft Research Machine Learning and Perception Seminars
Foundations of Neuromechanical Systems Biology: Combining engineering, biology, and mathematics to understand how we move
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Microsoft Research Machine Learning and Perception Seminars
Strategies for General Recognition
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Microsoft Research Machine Learning and Perception Seminars
The cost of principles
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Non-Parametric Conditional Random Fields in Computer Vision and Image Processing
Machine Learning @ CUED
Higher Order Learning for Classification in Emergency Situations
Microsoft Research Machine Learning and Perception Seminars
Lifts of Convex Sets and Cone Factorizations
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Annealing Between Distributions by Averaging Moments
Microsoft Research Machine Learning and Perception Seminars
Efficient Multi-dimensional Parametric Mincuts for Constrained MAP Inference
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
NLIP Seminar Series
Recursive Deep Learning for Modeling Semantic Compositionality
Microsoft Research Machine Learning and Perception Seminars
Noise estimation by PDE-constrained optimisation
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Platinum Genomes
Machine Learning Reading Group @ CUED
Random Forests: One tool for all your problems.
Machine Learning @ CUED
Applied statistical genetics and next-generation association studies
Machine Learning @ CUED
Applied statistical genetics and next-generation association studies
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Global microRNA level regulation of EGFR-driven cell-cycle protein network in breast cancer
⚠️ Note unusual day and time!
MRC Biostatistics Unit Seminars
MRC Centenary Lecture: Putting life into numbers - how statistical science has transformed health care
⚠️ A summer reception to follow
MRC Biostatistics Unit Seminars
Phase II/III clinical trials: Recent developments in methodology for trial design and analysis
Machine Learning Reading Group @ CUED
Modelling Nonlinear Dynamical Systems
Machine Learning @ CUED
The combinatorial structure of conditionally i.i.d. negative binomial processes directed by a beta process
MRC Biostatistics Unit Seminars
The value of CStat
MRC Biostatistics Unit Seminars
MRC Centenary Lecture: What's happening to the world?
Machine Learning Reading Group @ CUED
Adaptive Hamiltonian-based MCMC samplers
MRC Biostatistics Unit Seminars
MRC Centenary Lecture: Numbers are weapons: a self defence guide
jg691's list
Google's Approach to Building Relationships with Universities: Presentation and Talk by Dr David J Harper
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Petri nets as semi-quantitative modeling method to explore systems behavior of disease-related pathways
Machine Learning Reading Group @ CUED
Bayesian Nonparametrics in Real-World Applications: Statistical Machine Translation and Language Modelling on Big Datasets
MRC Biostatistics Unit Seminars
Semi Markov models under panel observation
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Genome-wide association studies: Lessons from studying a large clinical cohort
Machine Learning @ CUED
Matrix Concentration Inequalities via the Method of Exchangeable Pairs
Machine Learning @ CUED
Deep Gaussian Processes
MRC Biostatistics Unit Seminars
Causal mediation analysis with multiple mediators
Microsoft Research Machine Learning and Perception Seminars
Building Better Questionnaires with Probabilistic Modelling
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Approaches to statistical modeling of network data
MRC Biostatistics Unit Seminars
MRC Centenary Lecture: Failings in hierarchies of evidence for controversial health-policy decisions
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Mapping tumor heterogeneity and developmental trajectories using 40 markers at single cell resolution:
⚠️ Room change: 215 instead of lecture theatre (outside guests will need visitor ID)
MRC Biostatistics Unit Seminars
Large sample results for tiny significance levels
Statistics
Approximating Data
Computational and Systems Biology
The Ninth Annual Symposium of the Cambridge Computational Biology Institute
MRC Biostatistics Unit Seminars
Scalable network modelling for personalized medicine
Machine Learning Reading Group @ CUED
Sparsity: Beyond L1
Machine Learning @ CUED
Bayesian nonparametric methods for non-exchangeable data
Machine Learning Reading Group @ CUED
Reproducing Kernel Hilbert Spaces in Non-parametric Statistics
MRC Biostatistics Unit Seminars
Signal Identification for Rare and Weak Features: Higher Criticism or False Discovery Rates
Machine Learning @ CUED
Non-parametric Bayesian Chromatin State Segmentation
Machine Learning Reading Group @ CUED
An Introduction to Sum Product Networks
Microsoft Research Machine Learning and Perception Seminars
Austerity in MCM - Land : Cutting the computational Budget
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Microsoft Research Machine Learning and Perception Seminars
Fast Variational Inference in the Conjugate Exponential Family
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Fast Variational Inference in the Conjugate Exponential Family
Machine Learning Reading Group @ CUED
Bayesian Reinforcement Learning
Microsoft Research Machine Learning and Perception Seminars
Semantics\sqcap Scalability\models\bot? Are Semantics and Scalability Incompatible?
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Inferring causal mediators from omics data in the context of genetic and environmental variations
Machine Learning Reading Group @ CUED
Probabilistic Programming
Statistics Reading Group
Reproducing Kernel Hilbert Spaces in Non-parametric Statistics
⚠️ Note the unusual time and location to allow attendance at the RSS Ordinary meeting
MRC Biostatistics Unit Seminars
Statistical inference of virus phylodynamics
Microsoft Research Machine Learning and Perception Seminars
Warped Mixture Models for Meaningful Clustering and Bayesian Manifold Learning
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
An application of HDP And IBP for stream-based action recognition and high dimensional data
Statistics
The Bayesian Approach To Inverse Problems
Machine Learning @ CUED
Using Context and Insight for the Analysis of LittleData?
Machine Learning Reading Group @ CUED
Machine Learning in Speech Recognition
Computational and Systems Biology
Computational analyses of high-throughput spatial proteomics data
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The logic and variation in genomic regulatory networks
MRC Biostatistics Unit Seminars
Haplotype sharing and time to common ancestor: resolving various genetics problems including the studies of rare variants and disease susceptibility variants
Machine Learning Reading Group @ CUED
Fragmentation Coagulation
Statistics Reading Group
Minimax lower bound using Assouad's method
Computational and Systems Biology
Genome sequencing of transmissible cancers in dogs and Tasmanian devils
Machine Learning @ CUED
Feature allocations, probability functions, and paintboxes
Statistics
Optimization meets Statistics: Fast global convergence for high-dimensional statistical recovery
Machine Learning @ CUED
Modelling Reciprocating Relationships with Hawkes Processes
Machine Learning Reading Group @ CUED
Conditional Density Estimation
Computational and Systems Biology
Machine learning approaches to predicting protein-ligand binding
Microsoft Research Machine Learning and Perception Seminars
New probabilistic methods for inference of natural selection on regulatory sequences in the human genome
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Metabolic regulation of the stress response and the cancer cell's Warburg effect
Microsoft Research Machine Learning and Perception Seminars
Daniel’s Adventures in Computer Vision Land
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Statistics
Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator
Statistics Reading Group
Adaptive algorithms for Stratified Sampling Monte Carlo
⚠️ Note the earlier time and different room to allow attendance at the RSS Ordinary Meeting
Computational and Systems Biology
Methodological Challenges in the Pursuit of the Tree of Life
Statistics
Local Bilinear Multiple-Output Quantile Regression: from $L_1$ Optimization to Regression Depth
Machine Learning Reading Group @ CUED
RCC Planning
Computational and Systems Biology
Genome-wide approaches to study alternative splicing using RNA-seq data
Computational and Systems Biology
MPhil in Computational Biology Open Afternoon
MRC Biostatistics Unit Seminars
Conditional Density Estimation through Enriched Dirichlet Process Mixture Models
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Evolution of cellular networks: from interactions to phenotypes
Statistics
When Bayesians Can't Handle the Truth
Machine Learning Reading Group @ CUED
Discrete Optimization
Statistics Reading Group
Theory and applications of proper scoring rules
Computational and Systems Biology
Ecological niche modeling and infectious disease
Machine Learning @ CUED
Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Circulating tumour DNA as a biomarker of genetics alterations in cancer
Machine Learning Reading Group @ CUED
Advanced Sampling
Computational and Systems Biology
Integration of functional genomics and pathway information to elucidate deregulation of signal transduction and drugs' mode of action
MRC Biostatistics Unit Seminars
Causal inference and stratified medicine: an illustration of trial designs incorporating biomarker information for mechanisms evaluation
Machine Learning Reading Group @ CUED
NIPS Recap
Computational and Systems Biology
Evolution of post-translational networks
Machine Learning Reading Group @ CUED
NIPS Recap
Microsoft Research Machine Learning and Perception Seminars
From motion capture of interacting hands to video based rendering.
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Statistics
Minimax Lower Bounds
Machine Learning Reading Group @ CUED
Bayesian and Gradient Reinforcement Learning
MRC Biostatistics Unit Seminars
Generating partially synthetic data to protect confidentiality in survey microdata
Microsoft Research Machine Learning and Perception Seminars
Spectral Edge: Making the Invisible Visible
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Statistics
Stability
Machine Learning Reading Group @ CUED
Spectral Clustering
MRC Biostatistics Unit Seminars
Dimension reduction based on sliced inverse regression (SIR): a look at the special case when n ‹p
Machine Learning @ CUED
The combinatorial structure underlying a beta processes is that of a continuum of Blackwell-MacQueen urn schemes
Statistics
Interim Monitoring of Clinical Trials: Decision Theory, Dynamic Programming and Optimal Stopping
Machine Learning Reading Group @ CUED
Modern Neural Networks: the Hinton Camp
Machine Learning @ CUED
Learning of Milky Way Model Parameters Using Matrix-variate Data in a New Gaussian Process-based Method
Machine Learning Reading Group @ CUED
Distributional compositional models of semantics
Machine Learning @ CUED
Identification of causal effects
Microsoft Research Machine Learning and Perception Seminars
Towards ad hoc interactions with robots
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Probabilistic methods for biomolecular structure simulations
Statistics
Wavelet-based estimation of the long memory parameter in Gaussian non-gappy and gappy time series
Machine Learning Reading Group @ CUED
Completely Random Measures in Bayesian Nonparametrics
Computer Laboratory Systems Research Group Seminar
Distributed, Real-Time Bayesian Learning in Online Services
MRC Biostatistics Unit Seminars
Bayesian hierarchical models and recent computational development using Integrated Nested Laplace Approximation, with applications to pre-implantation genetic screening in IVF
Microsoft Research Machine Learning and Perception Seminars
From the Information Extraction Pipeline to Global Models, and Back
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Computational and Systems Biology
The Dog That Didn't Bark: How Computational Analysis of Complex Cell Signaling Data Can Find Surprising Critical Regulatory Nodes
⚠️ Please contact Dr. Julio Saez-Rodriguez if you wish to attend this talk as he will need to inform security
Machine Learning Reading Group @ CUED
Model selection in a large compositional space
⚠️ note: the first 45 mins will be planning and the talk will start at around 3:15pm
MRC Biostatistics Unit Seminars
Mendelian Randomization: the next ten years?
MRC Biostatistics Unit Seminars
Predictive analytic modelling in clinical trials (patient recruitment, randomization and drug supply)
MRC Biostatistics Unit Seminars
Modelling heterogeneity in gene expression using the matrix-variate normal distribution
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Network biology of cancer
Machine Learning @ CUED
Compressed Sensing Applications in Functional Magnetic Resonance Imaging
Microsoft Research Cambridge, public talks
Convergent and Scalable Algorithms for Expectation Propagation Approximate Bayesian Inference
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Multi-Label Learning with Millions of Categories
MRC Biostatistics Unit Seminars
Modelling the growth and transmission of infectious disease by linking epidemiology and population genetics
Machine Learning @ CUED
Efficient Sampling with Kernel Herding
Seminars on Quantitative Biology @ CRUK Cambridge Institute
From protein networks to disease mechanisms
Microsoft Research Machine Learning and Perception Seminars
Capture of dynamic scene using multiple cameras provides rich spatial-temporal information that can be used for solving challenging computer vision problems.
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Microsoft Research Machine Learning and Perception Seminars
Tell Me Where You’ve Lived and What You Want -- I’ll Tell You What You Like and Need
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Microsoft Research Machine Learning and Perception Seminars
Latent Hough Transform for Object Detection
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Frank-Wolfe optimization insights in machine learning
Microsoft Research Machine Learning and Perception Seminars
Context sensitive information: Which bits matter in data?
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Deep learning for vision: a case study for visual textures, and some thoughts on a general framework
Machine Learning @ CUED
Thermodynamics as a Theory of Decision-Making with Information Processing Costs
Microsoft Research Machine Learning and Perception Seminars
SmartDesign: Living with Geometric Complexity
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Human Behavior Classification with Infinite Hidden Conditional Random Fields
Microsoft Research Machine Learning and Perception Seminars
Part A: Non-parametric image optimization & Part B: Crowdsourcing gaze data collection
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Microsoft Research Machine Learning and Perception Seminars
Multi-Label Learning with Millions of Categories & Generalized Multiple Kernel Learning with a Million Kernels
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Inference Group
Data Modelling With Neural Networks (II): Content-Addressable Memories And State-Of-The-Art Error-Correcting Codes
⚠️ Last Lecture!
Microsoft Research Machine Learning and Perception Seminars
Prediction Strategies without Loss
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Plant Sciences 'ABC' Seminars
Characterising the evolutionary trajectories generating C4 photosynthesis through inference of phenotypic transition networks
Machine Learning @ CUED
Fast Gaussian process learning for regression, semi-supervised classification, and multiway analysis
Machine Learning @ CUED
Non-parametric Bayesian Learning of User Preferences: Elicitation, Sparsification and Beyond
Machine Learning @ CUED
Structured Prediction using Linear Programming Relaxations
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Variational Methods in 3+Dimensional Biomedical Imaging
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The life histories of 21 breast cancers
Inference Group
Advanced Monte Carlo Methods and Variational Inference
Machine Learning Reading Group @ CUED
Dependent normalized random measures
Machine Learning Reading Group @ CUED
GP-BUCB for Spinal Cord Injury Therapy: Batch Active Learning with Applications
MRC Biostatistics Unit Seminars
Optimal data combination in seamless Phase II/III clinical trials
Machine Learning @ CUED
Discovery of Complex Behaviors through Contact-Invariant Optimization
Statistics Reading Group
Graphical communication of variability, risk and uncertainty
Inference Group
Approximating Probability Distributions (I)-(II): Monte Carlo Methods and Variational Inference
⚠️ Two lectures!
Microsoft Research Machine Learning and Perception Seminars
The Inverted Multi-Index
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning Reading Group @ CUED
On Data (In-)Dependent Hashing
Statistics Reading Group
Modern advances in likelihood ratio inference
Inference Group
An Introduction to Statistical Inference, Data Modelling & Pattern Recogntion
⚠️ Two Lectures!
Statistics
Modelling Network Data
Machine Learning Reading Group @ CUED
Poisson Processes: Applications in Machine Learning
Computational and Systems Biology
Eighth Annual Symposium of the Cambridge Computational Biology Institute
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Biological Image Analysis Made Easy
⚠️ Note the unusual time: 11am not 4pm!
Machine Learning Reading Group @ CUED
A rough guide to the Aldous-Hoover representation theorem for exchangeable arrays
MRC Biostatistics Unit Seminars
Congenial multiple imputation of partially observed covariates within the full conditional specification framework
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The evolution of mammalian tissue transcriptomes
Machine Learning Reading Group @ CUED
Title to be confirmed
Machine Learning Reading Group @ CUED
Dirichlet Process Mixture Models and Bayesian Nonparametric Density Estimation
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Modeling stem cell differentiation on multiple scales
⚠️ Tuesday, not Monday!
Statistics
Grouping strategies for denoising
Machine Learning @ CUED
Learning with nonparametric dependence and divergence estimation
Inference Group
Communication over noisy channels (II)
Plant Sciences 'ABC' Seminars
Introduction to Metabolomics
Machine Learning @ CUED
Past work and future interests: respectively, the scattering of Anyons and Monte Carlo methods
Machine Learning Reading Group @ CUED
"Structured sparsity and convex optimization"
Machine Learning @ CUED
Non-parametric Bayesian Method and Maximum-A-Posteriori Inference in Statistical Machine Translation
Microsoft Research Machine Learning and Perception Seminars
Topic Models for Human Activity Understanding
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Inference Group
Communication over noisy channels (I)
Statistics
The distribution of the maximal difference between a Brownian bridge and its concave majorant
Machine Learning Reading Group @ CUED
Financial Problems tractable to Machine Learning Methods
Machine Learning Reading Group @ CUED
A Predictive Study of Bayesian Nonparametric Regression Models
MRC Biostatistics Unit Seminars
Setting sample size for common designs when evaluating interventions and biomarkers
⚠️ Note the earlier than usual start time
Machine Learning Reading Group @ CUED
Title to be confirmed
Machine Learning Reading Group @ CUED
Weighted Finite-state Automata
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Machine learning applications in genetic regulation and cancer
Machine Learning Reading Group @ CUED
Active Learning
Seminars on Quantitative Biology @ CRUK Cambridge Institute
ShrinkSeq: a flexible and powerful method for Bayesian analysis of RNAseq data
⚠️ Note the time change: 2pm (not 4pm)
Machine Learning Reading Group @ CUED
Topic Modelling
Machine Learning Reading Group @ CUED
Structural Learning of Dynamic Bayesian Networks
Plant Sciences 'ABC' Seminars
A Step-by-Step Guide to Phylogenetic Analysis
MRC Biostatistics Unit Seminars
How to use simulation studies in understanding and evaluating statistical methods
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Evolution of developmental gene expression programs
Microsoft Research Machine Learning and Perception Seminars
ORCHID: Human-agent collectives for disaster response and the smart grid
⚠️ o This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attendin
Machine Learning Reading Group @ CUED
Extended ensemble Monte Carlo
Machine Learning @ CUED
Infinite Structured Explicit Duration Hidden Markov Models
Machine Learning Reading Group @ CUED
"Symmetry and sufficiency"
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Modelling in systems genetics: computational approaches for discovering disease networks
Inference Group
Entropy and data compression (II)
⚠️ PLEASE NOTE: There will be no lectures during the Easter break (12 March - 9 April). Lectures will resume on 16 April.
Microsoft Research Machine Learning and Perception Seminars
Sequential Decision Making in Experimental Design and Sustainability via Adaptive Submodularity
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
MRC Biostatistics Unit Seminars
Some thoughts on multi-parameter evidence synthesis
Inference Group
Entropy and data compression (I)
Machine Learning @ CUED
Probabilistic computing: computation as universal stochastic inference, not deterministic calculation
Inference Group
Introduction to information theory
MRC Biostatistics Unit Seminars
Latent Mixture Quantile Regression for Longitudinal Data
Microsoft Research Machine Learning and Perception Seminars
Exploiting Variable Impedance for Robotics: Mimic or Optimize?
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
All CMS Events
Open Afternoon for the MPhil in Computational Biology
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Model Based Target Identification from Expression Data
Statistics Reading Group
Robust Statistics: An Overview and Some Questions
Computational and Systems Biology
Genome-Based Drug Discovery and Re-Purposing: a new golden age for DNA microarrays?
Machine Learning Reading Group @ CUED
Information bottleneck
⚠️ Please note the change in time. This RCC will take place at 15:00-16.30pm.
Statistics
Random forests
Machine Learning Reading Group @ CUED
Ensemble Methods in Machine Learning
MRC Biostatistics Unit Seminars
Which survival model? Model selection and model averaging issues for analysis of survival and event history data
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The Search for Organizing Principles in Cancer Systems Biology
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Increased methylation variation across cancer types
Machine Learning @ CUED
Scaling Machine Learning for the Internet
MRC Biostatistics Unit Seminars
Design and Analysis of Multi-Arm, Multi-Stage Clinical Studies
Seminars on Quantitative Biology @ CRUK Cambridge Institute
RNAi libraries for high throughput phenotyping and drug resistance screening in the African trypanosome
Microsoft Research Machine Learning and Perception Seminars
Closing the gap between weakly and fully supervised methods
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Computational and Systems Biology
Multi-scale studies on Drosophila transcription factors
Machine Learning @ CUED
Bayesian Quadrature for Prediction and Optimisation
Machine Learning @ CUED
Efficient MCMC for Continuous Time Discrete State Systems
Seminars on Quantitative Biology @ CRUK Cambridge Institute
RNAi-based molecular computing for cancer cell detection
Statistics
The aggregation problems in learning theory
Microsoft Research Machine Learning and Perception Seminars
Beyond the Piece of Cardboard: Learning to Adjust Photographs
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
A Maximum Entropy Perspective on Spectral Dimensionality Reduction
Machine Learning Reading Group @ CUED
Approximate Inference in Gaussian Process Models
Computational and Systems Biology
Approximate Bayesian Computation for evolution in a test tube
MRC Biostatistics Unit Seminars
Assessment of Trend in Recurrent Event Processes
Microsoft Research Machine Learning and Perception Seminars
PARIS: Probabilistic Alignment of Relations, Instances, and Schema
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Statistics Reading Group
Statistical problems in Astronomy and High Energy Physics
Computational and Systems Biology
tba
Microsoft Research Machine Learning and Perception Seminars
Probabilistic programs and the computability and complexity of Bayesian reasoning
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Statistics
On adaptation of false discovery rate
Machine Learning Reading Group @ CUED
Proper local scoring rules
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Inferring mechanisms of gene regulation from patterns of evolutionary divergence
Computational and Systems Biology
From batch effects and randomness to personalised stratified medicine
Machine Learning @ CUED
Variational Inference for Non-Conjugate Models
Machine Learning Reading Group @ CUED
Hyper and structural Markov laws for graphical models
MRC Biostatistics Unit Seminars
Modelling the transmission of Clostridium difficile in hospitals
Machine Learning @ CUED
Not so naive Bayesian classification
Microsoft Research Machine Learning and Perception Seminars
Exclusive Pólya Urns and their applications
⚠️ o This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attendin
Machine Learning @ CUED
Bayesian Nonparametrics: Latent Feature and Prediction Models, and Efficient Inference
Machine Learning @ CUED
Machine Learning Markets
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Chromatin-mediated regulation of gene expression in mouse ES cells
One Day Meeting - Seventh Annual Symposium of the Cambridge Computational Biology Institute
CCBI Annual Symposium
MRC Biostatistics Unit Seminars
Statistical Software at the Centre for Multilevel Modelling
Machine Learning @ CUED
Factored Shapes and Appearances for Parts-based Object Understanding AND Transformation Equivariant Boltzmann Machines
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Adult stem cell fate: a laboratory for statistical physics
Machine Learning @ CUED
Optimal Reinforcement Learning for Gaussian Systems
Machine Learning @ CUED
Exclusive Pólya Urns and their applications
Microsoft Research Machine Learning and Perception Seminars
Information-Greedy Global Optimisation
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Microsoft Research Machine Learning and Perception Seminars
Mechanism Design without Money via Stable Matching
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Microsoft Research Machine Learning and Perception Seminars
SocialFusion: Fusing Mobile, Sensor, and Social Computing in the Cloud To Enable Next-Generation Context-Aware Applications
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Approximate Bayesian Inference for Large Scale Inverse Problems: A Computational Viewpoint
Machine Learning @ CUED
Some Practical Reflections on Graphical Models
Microsoft Research Machine Learning and Perception Seminars
Principles of Humanoid Locomotion Control
⚠️ This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending
Machine Learning @ CUED
Beyond Keyword Search: Discovering Relevant Scientific Literature
Machine Learning @ CUED
Graphical Models for Bandit Problems
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Perturbation Biology of Cancer Cells
Machine Learning @ CUED
Bayesian regression and classification with multivariate sparsifying priors
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Phylogenetic Inference of Multidomain Evolution
MRC Biostatistics Unit Seminars
The Natural History and Predictive Factors of Long Term Outcomes in Systemic Lupus Erythematosus: Analysis from the Hopkins Lupus Cohort
Statistics Reading Group
Statistical image processing for electron microscopy on molecular machines
MRC Biostatistics Unit Seminars
Assessing surrogacy using linear mixed models and the surrogate threshold effect
Machine Learning @ CUED
An FX trading system using adaptive reinforcement learning
⚠️ (rescheduled from May 24th)
Statistics
Non-parametric regression with observations at imprecise times: Bayesian radiocarbon calibration
Machine Learning @ CUED
Censored Exploration in Dark Pools
Statistics Reading Group
Bayesian Clustering with the Dirichlet-Process Prior
Machine Learning Reading Group @ CUED
Connections between Gaussian Process Regression, Kalman filtering and RTS Smoothing
Machine Learning @ CUED
An FX trading system using adaptive reinforcement learning
⚠️ RESCHEDULED FOR JUNE 7th
Machine Learning Reading Group @ CUED
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
Statistics Reading Group
Nonparametric maximum likelihood estimation
MRC Biostatistics Unit Seminars
Experience and challenges of applying Bayesian methods in food safety risk assessments
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Allele specific expression design using short read DNA sequencing and application to the genetics of autoimmune disorders
Inference Group
Hierarchical hidden Markov models revisited
Machine Learning Reading Group @ CUED
Expectation Propagation for POMDP Spoken Dialogue Models
Statistics
Likelihood Inference and Bayesian MCMC
Statistics Reading Group
Exact simulation
Peter Whittle Lecture
An afternoon of Mathematics and Biology
Seminars on Quantitative Biology @ CRUK Cambridge Institute
CRUK computational biology day
Microsoft Research Machine Learning and Perception Seminars
Formal Methods in Synthetic Biology
Inference Group
Mandarin Dasher
Machine Learning @ CUED
Characterization of the Ewens-Pitman family of random partitions by a deletion property and a de Finetti-type theorem for exchangeable hierarchies
MRC Biostatistics Unit Seminars
Patterns of vulnerability in pregnancy and early childhood: Measurement, interactions, effect moderation and random coefficients in latent variable models
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Do modules or pathways help predict breast cancer outcome?
Microsoft Research Machine Learning and Perception Seminars
Enforcing topological constraints in energy-based image segmentation
Microsoft Research Machine Learning and Perception Seminars
On a first-order primal-dual algorithm with applications to convex problems in computer vision
Seminars on Quantitative Biology @ CRUK Cambridge Institute
From data to bench to bedside - prognostic markers and therapeutic targets in breast cancer
LMS Invited Lectures 2011
Compressed sensing: Lecture 8
LMS Invited Lectures 2011
Generalized sampling and infinite-dimensional compressed sensing
LMS Invited Lectures 2011
Compressed sensing: Lecture 7
LMS Invited Lectures 2011
Compressed sensing: Lecture 6
LMS Invited Lectures 2011
Minimisation of sparse higher-order energies for large-scale problems in imaging
LMS Invited Lectures 2011
Compressed sensing: Lecture 5
LMS Invited Lectures 2011
Compressed sensing: Lecture 4
LMS Invited Lectures 2011
The Dantzig selector for high dimensional statistical problems
LMS Invited Lectures 2011
Compressed sensing: Lecture 3
LMS Invited Lectures 2011
Compressed sensing: Lecture 2
Microsoft Research Cambridge, public talks
Machine Learning for WLAN Positioning
LMS Invited Lectures 2011
Compressed Sensing in RF
LMS Invited Lectures 2011
Compressed sensing: Lecture 1
Inference Group
Rigid body motion in conformal geometric algebra
Machine Learning @ CUED
Nonlinear Dynamics of Learning
Machine Learning Reading Group @ CUED
Exchangeability
MRC Biostatistics Unit Seminars
Sensitivity of parameter estimates of marginal and random-effects models to missing data
Machine Learning @ CUED
Exponential Conditional Volatility Models
Inference Group
CRH: a Central Reference Handling system
Machine Learning Reading Group @ CUED
Deep Belief Networks for Phone Recongition
Machine Learning @ CUED
Challenges in implementing the Bayesian paradigm
Computational and Systems Biology
Persistence and control of bTB in Great Britain
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Evidence of non-random mutation rates suggests a risk management strategy for bacterial evolution
Machine Learning @ CUED
Expectation Propagation in Sparse Linear Models with Spike and Slab Priors
Machine Learning @ CUED
Probabilistic matrix factorization for reconstruction of missing data
Machine Learning Reading Group @ CUED
The effect of normalization -- a case study in speech synthesis
Statistics Reading Group
Model criticism in complex Bayesian evidence synthesis for infectious disease models
Machine Learning @ CUED
Title to be confirmed
Machine Learning Reading Group @ CUED
Post-NIPS Highlight session
MRC Biostatistics Unit Seminars
A Causal Diagram Approach to Evidence Synthesis
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Intrinsically Unstructured Proteins: Regulation and Disease
Machine Learning Reading Group @ CUED
Optimal weighted nearest neighbour classifiers
Statistics Reading Group
Nonparametric maximum likelihood estimation
MRC Biostatistics Unit Seminars
Dropouts in the AB/BA crossover design
Machine Learning Reading Group @ CUED
Kernel Methods
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Theoretical models of the development of the nervous system
Inference Group
A computer-vision based facial gesture switch
Machine Learning Reading Group @ CUED
Machine Learning techniques in computer vision applications
Statistics Reading Group
Frameworks for causal inference
Computational and Systems Biology
Open Afternoon for MPhil in Computational Biology
Machine Learning @ CUED
Differential Geometric MCMC Methods
Statistics
Simultaneous local and global adaptivity of Bayesian wavelet estimators in nonparametric regression
Machine Learning Reading Group @ CUED
Infinite multiple relational models for complex networks
Machine Learning @ CUED
Mining viral datasets
Machine Learning Reading Group @ CUED
Completely Random Measures
Cancer Research UK Cambridge Centre Lectures in Cancer Biology and Medicine
Systems approaches to understanding transcriptional regulation
Machine Learning @ CUED
Universal Bayesian Agents: Theory and Applications
Machine Learning @ CUED
Machine learning in cancer research (a.k.a CRI meets CUED)
⚠️ (note new date)
Machine Learning @ CUED
Novi Quadrianto
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Using association-based genetics to understand basic biology
Inference Group
Introduction to Geometric Algebra II
Machine Learning Reading Group @ CUED
Submodularity for Machine Learning
Computational and Systems Biology
Mathematical models of signaling networks and their application to disease
MRC Biostatistics Unit Seminars
Spatial prediction in the presence of positional error
Microsoft Research Machine Learning and Perception Seminars
Handling temporal variation of unknown characteristics in streaming data analysis.
Machine Learning @ CUED
Learning item trees for collaborative filtering with implicit feedback
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Integrative Network Biology and Cellular Information Processing
Inference Group
Title to be confirmed
Machine Learning @ CUED
Non-Smooth-Norm Image Reconstruction from Noisy Data
Machine Learning Reading Group @ CUED
NIPS Highlight Session
Machine Learning Journal Club
Machine Leaning Journal Club
Statistics
On adaptive nonparametric inference
Machine Learning Reading Group @ CUED
Poisson Processes
Machine Learning @ CUED
Crowdsourcing data modelling
Computational and Systems Biology
Modelling epidemics: mixing patterns, changing behaviour, and swine flu
MRC Biostatistics Unit Seminars
Modelling Relative Survival: Flexible Parametric Models and the Estimation of Net and Crude Mortality
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The evolution and regulation of gene expression levels in mammals
Inference Group
Out-of-band Language Modelling
Machine Learning Reading Group @ CUED
Convex Optimisation
Microsoft Research Machine Learning and Perception Seminars
Bayesian Inference with Kernels
Computational and Systems Biology
Decoding Genetic Switches in T Helper Cell Differentiation
Inference Group
South Africa's Involvement With Square Kilometre Array Bid: Infrastructure and Electromagnetic Quietness
Machine Learning @ CUED
Short talks: Mixed Cumulative Distribution Networks; Nonparametric Bayesian community discovery in social networks; Expectation Propagation for Dirichlet Process Mixture Models
Machine Learning Reading Group @ CUED
An Introduction to Bayesian Statistics
Computational and Systems Biology
Executable Strategies for Cellular Decision Making
MRC Biostatistics Unit Seminars
The competing explanations: Frailty or individual development? Examples from cancer and from network theory
Microsoft Research Machine Learning and Perception Seminars
Affective Technology
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Finding interesting clusters using Bayesian data fusion
Inference Group
The Multiscale Composite Dirichlet Process and its applications
Physics of Medicine (PoM) Seminar Series
STORM below the localisation limit
Inference Group
Putting Some Language Back Into Language Modelling
MRC Biostatistics Unit Seminars
Modeling longitudinal observations with excess zeros and measurement error, with application to nutritional epidemiology
Machine Learning Reading Group @ CUED
Herding or a '3rd way to learn'
MRC Biostatistics Unit Seminars
Badger culling to control bovine TB - its potential role in a science-led policy
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Deconvolving the epigenome
Machine Learning Reading Group @ CUED
Advanced Scientific Programming in Python
Computational and Systems Biology
Why is genomics now unfashionable in drug discovery?
Inference Group
Bayesian Psychometry
Machine Learning Reading Group @ CUED
Unsupervised Grammar Induction
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Transcriptional characterization of glioma stem cells using high-throughput tag sequencing
Inference Group
Continuous Gesture Recognition and Visualization
Machine Learning @ CUED
Searching for Knowledge Instead of Web Pages
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Evolutionary Signatures of Strand Specific Mutagenic Processes
Machine Learning @ CUED
Bayesian Inference with Kernels
Inference Group
Title to be confirmed
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Unexpected complex dynamics of cellular transcriptional response
Inference Group
Ticker: Case Study
Machine Learning @ CUED
On the Equivalence of Graph Cuts and Max-product Belief Propagation
Inference Group
Statistical Language Modelling
Inference Group
Title to be confirmed
Inference Group
Topic Models -- and how to break them
Microsoft Research Cambridge, public talks
Information Asymmetries in Pay-Per-Bid Auctions: How Swoopo Makes Bank
Wednesday Seminars - Department of Computer Science and Technology
Some Uses of Hashing in Networking Problems
Machine Learning @ CUED
Culture wars, voting and polarization: divisions and unities in modern American politics
⚠️ general audience talk (non-technical) -- NOTE change of room to LR4!
Machine Learning @ CUED
Creating structured and flexible models: some open problems
Machine Learning @ CUED
Efficient Bayesian analysis of multiple changepoint models
Inference Group
Approximate Inference for the Loss-Calibrated Bayesian
Machine Learning @ CUED
Learning Common Grammar from Multilingual Corpus / Online Multiscale Dynamic Topic Models
Machine Learning @ CUED
Scalable Parallel Computing with CUDA
Inference Group
Introduction to Geometric Algebra
Inference Group
Dasher on a Space-filling curve
Machine Learning @ CUED
Using transformed domains to sparsify Gaussian Processes
Machine Learning @ CUED
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Uncovering signaling differences between normal and transformed hepatocytes using cell-specific pathway models
Inference Group
Bayesian head pose estimation
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Accelerated substitution rates in non-coding sequence: Gene duplication, transcription factor binding site turnover and biased gene conversion.
MRC Biostatistics Unit Seminars
Model-based cluster analysis for structured data
MRC Biostatistics Unit Seminars
Modelling health scores with the multivariate skew normal
Seminars on Quantitative Biology @ CRUK Cambridge Institute
A quantitative view of gene expression levels and epigenetic modifications
Inference Group
Differential Privacy and Probabilistic Inference
Machine Learning @ CUED
Natural Conjugate Gradient Learning for Fixed-Form Variational Bayes
Machine Learning @ CUED
Sparse Factor Analysis Applied to Three Biological Problems
Machine Learning @ CUED
Using topic models to help cure cancer
Machine Learning Reading Group @ CUED
Structured Learning and Structural SVMs
Machine Learning @ CUED
Structured Prediction Cascades
Machine Learning @ CUED
Parametric Bandits, Query Learning, and the Haystack Dimension
Seminars on Quantitative Biology @ CRUK Cambridge Institute
ChIP-Seq in six Drosophila species reveals a highly similar binding landscape for the developmental transcription factor Twist.
Statistics
Introduction to adaptive estimation
Machine Learning Reading Group @ CUED
Conditional Random Fields : Theory and Application
Inference Group
Robust Associative memory
Statistics
Approximation by Log-Concave Distributions
Inference Group
Conditional Counting: Approximate Multinomial Probit Regression
Machine Learning Reading Group @ CUED
Topics in Statistical Machine Translation
One Day Meeting - 6th Annual Symposium of the Cambridge Computational Biology Institute
From phenotypes to pathways: inferring genetic architecture from perturbation maps
Statistics Reading Group
Online Expectation-Maximisation
One Day Meeting - 6th Annual Symposium of the Cambridge Computational Biology Institute
Title to be confirmed
One Day Meeting - 6th Annual Symposium of the Cambridge Computational Biology Institute
Quantifiying Adaptive Evolution in the Drosophila Immune System
One Day Meeting - 6th Annual Symposium of the Cambridge Computational Biology Institute
Title to be confirmed
One Day Meeting - 6th Annual Symposium of the Cambridge Computational Biology Institute
Gene Expression in Aneuupoid Drosophila
One Day Meeting - 6th Annual Symposium of the Cambridge Computational Biology Institute
Title to be confirmed
One Day Meeting - 6th Annual Symposium of the Cambridge Computational Biology Institute
Title to be confirmed
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Dynamics of molecular clocks expose the lineage relations of cells
Machine Learning Reading Group @ CUED
Title to be confirmed
MRC Biostatistics Unit Seminars
Harnessing social networks for HIV surveillance
Inference Group
Coherent Inference on Optimal Play in Games
Statistics
Sparse NonGaussian Component Analysis
Statistics Reading Group
Recent Advances in Particle Based Simulation Methods
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Deep sequencing reveals differential expression of microRNAs in favorable versus unfavorable neuroblastoma
Inference Group
Report from CHI 2010
Machine Learning Reading Group @ CUED
Bundle methods and its application in machine learning
MRC Biostatistics Unit Seminars
A flexible regression approach using GAMLSS
Seminars on Quantitative Biology @ CRUK Cambridge Institute
A global map of human gene expression
One Day Meeting - 6th Annual Symposium of the Cambridge Computational Biology Institute
Ultrasound elastography
One Day Meeting - 6th Annual Symposium of the Cambridge Computational Biology Institute
Title to be confirmed
Inference Group
Speech Dasher: Fast Writing using Speech and Gaze
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Title to be confirmed
Inference Group
Language Modelling with PPM
Machine Learning Reading Group @ CUED
Sparsification for Gaussian Processes for Regression
MRC Biostatistics Unit Seminars
Some issues for causal inference in observational epidemiology
Machine Learning @ CUED
Slice sampling with latent Gaussian models
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Learning the structure of graphical models with latent variables
Inference Group
Bayesian feature tracking and head pose estimation
Statistics
Asymptotic equivalence and sufficiency for volatility estimation under microstructure noise
Machine Learning Reading Group @ CUED
Title to be confirmed
Machine Learning @ CUED
Dynamic Network Tomography: Model, Algorithm, Theory, and Application
Machine Learning @ CUED
Making Sense of Data - A Research Agenda
Computational and Systems Biology
Characterization of 1000 breast cancer genomes and transcriptomes
Machine Learning @ CUED
Subspace Codes for Adversarial Error-Correction in Network Coding
⚠️ short talk
Machine Learning @ CUED
Bayesian Inference in Networks of Queues
Machine Learning @ CUED
Stochastic Outlier Selection
All CMS Events
"Bioinformatics in the Pharmaceutical Industry"
Inference Group
Neurally-inspired Computing
Statistics Reading Group
Variational methods continued
Computational and Systems Biology
Title to be confirmed
Inference Group
Latent Force Models with Gaussian Processes
MRC Biostatistics Unit Seminars
Regret-regression for optimal dynamic treatment regimes
Inference Group
Dasher
Statistics
On combinatorial testing problems
Machine Learning Reading Group @ CUED
Title to be confirmed
Statistics Reading Group
An Introduction to Variational Methods for Approximate Inference in Graphical Models
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Next generation computing for next generation sequencing
Machine Learning Reading Group @ CUED
Semi supervised learning
Cancer Research UK Cambridge Centre Lectures in Cancer Biology and Medicine
Why computational biology is useful in the cancer world
Statistics
Compressed sensing in infinite dimensions
Machine Learning Reading Group @ CUED
Variational inference in graphical models: The view from the marginal polytope
Statistics Reading Group
Reversible jump MCMC
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Analysing the pharmacokinetics and pharmacodynamics of drugs in vivo by upgrading in vitro data based on mathematical modelling
Inference Group
NIPS 2009 highlights
Statistics
Thick-pen transformation for time series
Machine Learning Reading Group @ CUED
The Fractional Belief Propagation menace
HEP phenomenology joint Cavendish-DAMTP seminar
Accelerated Bayesian inference in cosmology
Machine Learning Reading Group @ CUED
(Canceled) A Causal Calculus for Statistical Research
⚠️ Canceled
Statistics Reading Group
New approaches to Bayesian asymptotics
Machine Learning @ CUED
Machine Learning Course (4F13)
⚠️ 4F13 course - repeats Wed, Thurs at 10am during Lent
MRC Biostatistics Unit Seminars
Modelling the association between patient characteristics and the change over time in a disease measure using observational cohort data
Machine Learning Reading Group @ CUED
RCC Planning Meeting
Machine Learning @ CUED
Machine Learning Course (4F13)
⚠️ 4F13 course - repeats Wed, Thurs at 10am during Lent
Inference Group
Title to be confirmed
Seminars on Quantitative Biology @ CRUK Cambridge Institute
New Approaches to Biomedical Data Modelling: An Introductory Tutorial
Machine Learning Reading Group @ CUED
Unbounded-depth hierarchical Pitman-Yor processes
MRC Biostatistics Unit Seminars
Emulation of random output (stochastic) models: theory and application
Inference Group
NIPS poster
Inference Group
Face Recognition: Who's That Blonde?
Statistics
Learning rates in Bayesian nonparametrics: Gaussian process priors
⚠️ Joint with Probability Series
Machine Learning Journal Club
Journal Club: Visualizing Data using t-SNE
Machine Learning Reading Group @ CUED
Learning rates in Bayesian nonparametrics
Statistics Reading Group
An introduction to sequential Monte Carlo methods
Inference Group
Probabilistic feature tracking with non-probabilistic techniques
Machine Learning @ CUED
Indian Buffet Processes with Power-law Behaviour
Machine Learning Journal Club
The Infinite Gaussian Mixture Model
Machine Learning @ CUED
Gaussian Processes for Active Data Selection, Faults, Changepoints and Sensor Selection
Inference Group
研究の紹介
Machine Learning Reading Group @ CUED
Bayesian Agglomerative Clustering with Coalescents
Statistics Reading Group
Compressed Sensing - Introduction and Future Aspects
MRC Biostatistics Unit Seminars
Generalized estimating equations for censored data
Machine Learning @ CUED
KL control theory and decision making under uncertainty
Machine Learning Journal Club
Oscillations, Phase-of-firing Coding and STDP: An Efficient Learning Scheme (Journal club)
Machine Learning Reading Group @ CUED
Machine Learning RCC - Bayesian Agglomerative Clustering with Coalescents, Teh, Daumé and Roy, NIPS 2007
Statistics
Soap film smoothing
Machine Learning Reading Group @ CUED
Filtering of Noisy Time-Series Data
MRC Biostatistics Unit Seminars
The Value for Medical and Public Health Decisions of Adding Single Nucleotide Polymorphism Data to a Model for Breast Cancer Risk
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Biochemical network reconstruction from data
Inference Group
Optimizing Dasher for the iPhone
Statistics
Risk Hull Methods for Inverse Problems
Machine Learning Journal Club
Bayesian integration in sensorimotor learning
Machine Learning Reading Group @ CUED
Speed Reviewing
Statistics Reading Group
Bayesian Nonparametric Mixture Models
Machine Learning @ CUED
Information theoretic model selection in clustering
MRC Biostatistics Unit Seminars
Estimation of time to pregnancy from current duration data
Inference Group
A facial gesture switch using hidden Markov models
Statistics
Bayesian Methods in Cosmology
Machine Learning Journal Club
Distilling Free-Form Natural Laws from Experimental Data
Machine Learning Reading Group @ CUED
High-dimensional variable selection via sure independence screening
Machine Learning Journal Club
Machine Learning Book Club
Statistics
Forward Smoothing using Sequential Monte Carlo with Application to Recursive Parameter Estimation
MRC Biostatistics Unit Seminars
A Bayesian dose-escalation procedure for phase I/II clinical trials
Inference Group
Inclusive user modelling
Statistics
Choosing a good histogram
Machine Learning Journal Club
Journal club: Measurement integration under inconsistency for robust tracking
Machine Learning Reading Group @ CUED
Ensemble Methods in Machine Learning
Statistics Reading Group
When can we quantify uncertainty?
Machine Learning Journal Club
Machine Learning Book Club
Inference Group
Learning Logical Relations
Statistics
Total variation and curves
Machine Learning @ CUED
Motor Skills Learning for Robotics
Machine Learning Reading Group @ CUED
Structured prediction using energy-based models
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Cancer Tumour/Normal Pair Analysis with the Illumina Genome Analyzer
Inference Group
Recognition and Correction of Voice Web Search Queries
Machine Learning Journal Club
The Mondrian Process
Machine Learning Reading Group @ CUED
Technical Writing II
Machine Learning @ CUED
Coconut: Optimizing computations for machine learning
Inference Group
Of Uncertain Value -- Bayesian Quadratic Reinforcement Learning
Machine Learning Journal Club
COGAIN'09 proceedings
Machine Learning Journal Club
Machine Learning Book Club
Inference Group
Capacity of Spiking Neural Networks
Machine Learning Journal Club
Speed dependent automatic zooming for browsing large documents
Machine Learning Journal Club
Machine Learning Book Club
Inference Group
Thermal expansion of beta-eucryptite
Machine Learning Journal Club
Single Image Haze Removal using Dark Channel Prior
Seminars on Quantitative Biology @ CRUK Cambridge Institute
Towards a transcriptional taxonomy of in vitro stem cell preparations
Machine Learning Journal Club
Bursty and Hierarchical Structure in Streams.
Machine Learning @ CUED
Convex Variational Bayesian Inference for Large Scale Generalized Linear Models
Machine Learning Journal Club
Machine Learning Book Club
Inference Group
Text entry performance of state of the art unconstrained handwriting recognition: a longitudinal user study
Machine Learning Journal Club
Correlation, Causation, Model Comparison and Interventions
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning Journal Club
Machine Learning Book Club
Inference Group
Combining Collaborative Filtering with Meta Data for Scalable Recommendations
⚠️ Note unusual time
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning @ CUED
Computable Probability Theory
Inference Group
Physics Dimensions in Sage
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning Journal Club
Machine Learning Book Club
Inference Group
Dashing this way and that
Machine Learning Journal Club
Machine Learning Book Club
Inference Group
Mapping facial gestures to control cursors and switches
Machine Learning Reading Group @ CUED
Hessian-based Markov-Chain Monte Carlo Algorithms
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning Journal Club
Machine Learning Book Club
CoSBi Computational and Systems Biology Series
Analyzing the effect of noise on various models of Circadian Clock and Cell Cycle coupling
Inference Group
A quick way to learn a mixture of exponentially many linear models
⚠️ Note unusual time
Statistics
Working with over-parameterized models
Inference Group
Short ICML Practice Talk
Machine Learning Reading Group @ CUED
Slice Sampling
CoSBi Computational and Systems Biology Series
Topological keystone species: network analysis in modern systems ecology
Machine Learning Journal Club
Machine Learning Book Club
MRC Biostatistics Unit Seminars
Generalized Multilevel Functional Regression
CoSBi Computational and Systems Biology Series
Complexity and Robustness in Colonies of Agents: A Formal Languages and a Game Theory Approach
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The Executable Pathway to Biological Networks
Statistics Reading Group
The Dantzig Selector
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning @ CUED
Using gradient descent for optimization and learning
Statistics
Second Generation Wavelets and Astrophysics
Machine Learning Reading Group @ CUED
Technical Writing
CoSBi Computational and Systems Biology Series
Study disease-causing genes based on protein-protein interaction networks
Machine Learning Journal Club
Machine Learning Book Club
MRC Biostatistics Unit Seminars
The use of baseline covariates in cross-over studies
CoSBi Computational and Systems Biology Series
Stochastic simulation algorithms and analysis of biological systems
Cambridge Next Generation Sequencing Bioinformatics Day
Next Generation Sequencing Bioinformatics Day: Drinks & Flip Chart Session
Cambridge Next Generation Sequencing Bioinformatics Day
Next Generation Sequencing Bioinformatics Day Keynote 2: Dark matter and the dark arts
Cambridge Next Generation Sequencing Bioinformatics Day
Next Generation Sequencing Bioinformatics Day: Future Steps
Cambridge Next Generation Sequencing Bioinformatics Day
Next Generation Sequencing Bioinformatics Day Workshop 4: Counting and comparing
⚠️ Workshop covers peak calling, segmentation , enrichment, differential expression, normalisation, transcriptomics, ChIPseq.
Machine Learning Journal Club
Optimal Bayesian Reinforcement Learning on Trees
Cambridge Next Generation Sequencing Bioinformatics Day
Next Generation Sequencing Bioinformatics Day Workshop 3: Assembly / Structural variation
⚠️ Workshop covers de novo assemblers, paired end data, integrating data from different technologies, structural variation.
Cambridge Next Generation Sequencing Bioinformatics Day
Next Generation Sequencing Bioinformatics Day: Lunch & Flip Chart Session
Cambridge Next Generation Sequencing Bioinformatics Day
Next Generation Sequencing Bioinformatics Day Workshop 2: Alignment
⚠️ Workshop covers: Speed, sensitivity, alignment formats, repeats, SNPs, indels.
Cambridge Next Generation Sequencing Bioinformatics Day
Next Generation Sequencing Bioinformatics Day Keynote 1: Computational issues in ancient genomics
Cambridge Next Generation Sequencing Bioinformatics Day
Next Generation Sequencing Bioinformatics Day Workshop 1: Data Production
⚠️ Workshop covers Primary pipeline processing: quality scores, multiplexing; Data management: metadata, data storage, data delivery.
Cambridge Next Generation Sequencing Bioinformatics Day
Next Generation Sequencing Bioinformatics Day: Registration
Statistics
Particle Learning
Machine Learning Reading Group @ CUED
Divergence measures and message passing
CoSBi Computational and Systems Biology Series
Model Abstraction Methodology for Temporal Behavior Analysis of Multiscale Biological Systems
Machine Learning Journal Club
Machine Learning Book Club
CoSBi Computational and Systems Biology Series
Chemotaxis. Do we understand it all?
Seminars on Quantitative Biology @ CRUK Cambridge Institute
The Code Underlying Tissue-Regulated Splicing
Statistics
Default priors and model parametrization
Machine Learning Reading Group @ CUED
The IBM approach to speech separation
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning Reading Group @ CUED
Parsing Images the UCLA Way
Inference Group
Useful Computation with Coincidence Detection
Machine Learning Journal Club
Machine Learning Book Club
MRC Biostatistics Unit Seminars
Individual Prediction in Prostate Cancer Studies Using a Joint Longitudinal-Survival Model
Statistics
Handling Sparsity via the Horseshoe
Machine Learning Reading Group @ CUED
Hilbert space embedding of probability distributions
Inference Group
Bayesian periodicity detection
CoSBi Computational and Systems Biology Series
Dynamics of cell cycle transitions
CoSBi Computational and Systems Biology Series
Exploiting non-Markovian Bio-Processes within BlenX
Inference Group
Deducing Principles in Natural Perception
Machine Learning Journal Club
Machine Learning Book Club
CoSBi Computational and Systems Biology Series
A parallel perspective of the dynamics of biological reactive systems
Machine Learning Journal Club
Machine Learning Book Club
CoSBi Computational and Systems Biology Series
KInfer and BetaWB: tools for supporting the modeling workflow of Biological Systems
CoSBi Computational and Systems Biology Series
A Framework study of the NF-kB signalling pathway
Machine Learning @ CUED
Learning from Measurements in Exponential Families
Machine Learning Journal Club
Machine Learning Book Reading Club
CoSBi Computational and Systems Biology Series
On the deduction of chemical reaction rate constants from measurements of time series of concentration
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning Reading Group @ CUED
Bregman Divergences and Machine Learning
Inference Group
Geothermal power in Australia
Inference Group
Cloud Ships for global warming reduction
Statistics Reading Group
The EM algorithm and applications
Inference Group
Painless Parse Errors
CoSBi Computational and Systems Biology Series
Evolutionary computation: optimization and inference
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning @ CUED
Shrinkage regression for multivariate inference with missing data, with an application to portfolio balancing
MRC Biostatistics Unit Seminars
Hypothesis testing and estimation in a group sequential phase II/III clinical trial
CoSBi Computational and Systems Biology Series
Visual systems biology: design, understand, organize
Machine Learning @ CUED
Quasi-linear Sensor Management
Statistics
Do New Roads Generate Traffic?
Machine Learning Reading Group @ CUED
The Convex Concave Procedure
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning Reading Group @ CUED
Hybrids of Generative and Discriminative Models (Cont)
Statistics Reading Group
Ferguson's 1973 paper on the Dirichlet process
Machine Learning Journal Club
Machine Learning Book Reading Club
MRC Biostatistics Unit Seminars
Lessons from livestock - some things animal movements can tell us about social networks in epidemiology
Optimization and Incentives Seminar
A Survey of Results for Deletion Channels and Related Synchronization Channels
⚠️ Joint With Probability Seminar Series.
Kuwait Foundation Lectures
Bloom Filters, Related Data Structures, and their Applications
Machine Learning @ CUED
Generalization in Learning
Machine Learning Reading Group @ CUED
Large Margin Training of Hidden Markov Models
Machine Learning Journal Club
Machine Learning Book Club
Machine Learning @ CUED
Stochastic control as an inference problem
Computational and Systems Biology
Linked Oscillators in Circadian Biology
Machine Learning Reading Group @ CUED
Hybrid of Generative and Discriminative Models
Statistics Reading Group
Learning based on Data Compression
Machine Learning Reading Group @ CUED
Divergence measures and message passing - CANCELLED
⚠️ Canceled
Inference Group
More NIPS highlights
Computational and Systems Biology
Open Afternoon for MPhil in Computational Biology
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning Journal Club
Predicting and understanding the stability of G-Quadruplexes
Machine Learning @ CUED
Extending the Affinity Propagation Model
Machine Learning Reading Group @ CUED
Distributed Computing for Machine Learning
Statistics Reading Group
The 1995 Benjamini and Hochberg paper on false discovery rates
Inference Group
NIPS Highlights
Computational and Systems Biology
Better multiple sequence alignment by being phylogeny-aware, and better base calling from next-generation sequencers
Machine Learning Journal Club
Machine Learning Book Reading Club
MRC Biostatistics Unit Seminars
Estimating the impact of school closure on influenza transmission from sentinel data
Machine Learning Reading Group @ CUED
A Hierarchical Bayesian Language Model based on Pitman-Yor Processes
Computational and Systems Biology
Pathogen Genome Sequencing at the Sanger Institute
CoSBi Computational and Systems Biology Series
On Automatic Quantitative Verification of Biological Systems
⚠️ Time changed
Machine Learning @ CUED
The Block Diagonal Infinite Hidden Markov Model
CoSBi Computational and Systems Biology Series
BlenX, a language based approach for modelling biological systems
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning @ CUED
Probabilistic Graph Models for Debugging Software
Machine Learning Reading Group @ CUED
Probabalistic Inference for solving (PO)MDPs
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning @ CUED
HMMs for Protein Sequencing from Mass Spectrometry Data
Machine Learning Reading Group @ CUED
NIPS Offline Conference
MRC Biostatistics Unit Seminars
The Error Statistical Philosophy
Inference Group
Optimizing Similarity Functions in Various Pattern Recognition Problems
⚠️ Note unusual time
Inference Group
Visual Search: Applications and Computational Modelling
Inference Group
Eye-Tracking in Virtual Reality
Machine Learning @ CUED
Mondrian Processes
Inference Group
Estimating the Pen Trajectories of Handwritten Static Scripts using Hidden Markov Models
Machine Learning Reading Group @ CUED
An Introduction to Relational Learning
Cavendish Physical Society
Power to Choose: How the energy choices people make will change their lives.
Machine Learning Journal Club
Machine Learning Book Reading Club
MRC Biostatistics Unit Seminars
Bayesian meta-analysis of genetic association studies using Stata
Machine Learning Journal Club
Journal Club: Mixed Membership Stochastic Blockmodels
Statistics
Projective Limits of Bayes Equations
Machine Learning Reading Group @ CUED
Bayesian Reinforcement Learning in Continuous POMDPs
Statistics Reading Group
The 1995 wavelet paper of Donoho, Johnstone, Kerkyacharian and Picard
Computational and Systems Biology
"Studying human variation from whole genome sequence data".
Inference Group
Bayesian Inductive Programming
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning @ CUED
Hardness Ratios
Machine Learning Reading Group @ CUED
Cluster Analysis of Heterogeneous Rank Data
Computational and Systems Biology
" The dynamics of parasite-mediated competition"
Machine Learning Journal Club
Machine Learning Book Reading Club
CoSBi Computational and Systems Biology Series
Exactness and Approximation of the Stochastic Simulation Algorithm
CoSBi Computational and Systems Biology Series
Colonies of Synchronizing Agents: Computability and Robustness
Machine Learning Journal Club
Value Propagation: A Graphical Model for Bayesian Reinforcement Learning
Statistics
Sampling bias in logistic models
SciComp@Cam: Scientific Computing in Cambridge
Title to be confirmed
Machine Learning Reading Group @ CUED
Gaussian Process Latent Variable Models
Statistics Reading Group
Ronald Fisher's 1934 likelihood and inference paper
Computational and Systems Biology
Title to be confirmed
Inference Group
Thermochemistry and Nuclear power - Clean responsive electricity
Machine Learning @ CUED
Consensus finding, exponential models and infinite rankings
Machine Learning Journal Club
Machine Learning Book Reading Club
MRC Biostatistics Unit Seminars
Modeling relationships between food intakes and health-related outcomes: zero-inflated data subject to measurement error
Machine Learning Journal Club
Spiking Boltzmann Machines
Machine Learning Reading Group @ CUED
Point Process Intensity Estimation with GP's
Computational and Systems Biology
Type 1 Diabetes research, before and after association studies
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning Journal Club
A Precision-Click Method for Multiple-Choice Problems
Machine Learning Reading Group @ CUED
Knows What It Knows: A Framework For Self-Aware Learning
Statistics Reading Group
David Cox's 1972 proportional hazards paper
Computational and Systems Biology
Simultaneous Determination of Protein Structure and Dynamics
Inference Group
Low-cost large-scale renewable energy
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning @ CUED
Foundations of Nonparametric Bayesian Methods (Part III)
Machine Learning Journal Club
The discovery of structural form
Statistics
Simultaneous Confidence Band and Hypothesis Test in Generalised Varying-Coefficient Models
Machine Learning Reading Group @ CUED
Approximating the Kullback-Leibler Divergence Between GMMs
Wednesday Seminars - Department of Computer Science and Technology
Forensic Genomics:Kin Privacy, Driftnets and Other Open Questions
Microsoft Research Computational Science Seminars
What makes cellular decisions irreversible?
Machine Learning @ CUED
Efficient Sequential Monte Carlo Inference for Kingman's Coalescent
⚠️ Note unusual time
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning @ CUED
Context in human robot interaction
MRC Biostatistics Unit Seminars
Multiply robust estimation of statistical interaction parameters
CoSBi Computational and Systems Biology Series
Computational analysis of the connection between cell cycle and circadian rhythm
Statistics
Uniform limit theorems for wavelet density estimators
⚠️ joint Statistics/Probability Seminar
CUED Control Group Seminars
Learning to Control
SciComp@Cam: Scientific Computing in Cambridge
Title to be confirmed
Statistics Reading Group
Charles Stein's 1956 inadmissibility paper
Machine Learning @ CUED
Foundations of Nonparametric Bayesian Methods (Part II)
Machine Learning Reading Group @ CUED
To Naive Bayes or to Logistically Regress: That is the Question
MRC Biostatistics Unit Seminars
Transdimensional sampling algorithms for Bayesian variable selection in classification problems with many more variables than observations
Machine Learning @ CUED
Foundations of Nonparametric Bayesian Methods (Part I)
Machine Learning @ CUED
Shared Segmentation of Natural Scenes using Dependent Pitman-Yor Processes
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning Reading Group @ CUED
Condition Monitoring
Horizon: Bioengineering
Cambridge Stem Cell Initiative
Horizon: Bioengineering
Cambridge Physics of Medicine Initiative
⚠️ registration is required for this event
Horizon: Bioengineering
Applications of physical science to biological systems: droplets and fragments
Horizon: Bioengineering
Strategies for bringing back function to the damaged nervous system
⚠️ Medical Engineering (registration is required for this event)
Horizon: Bioengineering
Closing on closed-loop insulin delivery: Artificial Pancreas - where we are and where we go
⚠️ Medical Engineering
Horizon: Bioengineering
Health Technologies KTN: working together to accelerate innovation in healthcare
Horizon: Bioengineering
Collagen mechanics: from basic understanding to clinical applications
⚠️ registration is required for this event
Horizon: Bioengineering
Systems Biology: from models (and model organisms) to medicines
Computational and Systems Biology
RNA editing in plant organelles: Correlation between editing sites and protein three-dimensional structures
⚠️ Ectopic seminar - N.B. in Biochemistry Department
Machine Learning @ CUED
Spoken Dialogue Management
Machine Learning @ CUED
A Bayesian approach to language learning
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning @ CUED
Learning Bigrams from Unigrams
Machine Learning Journal Club
Machine Learning Book Reading Club
SciComp@Cam: Scientific Computing in Cambridge
Development tools for mobile devices
Machine Learning Reading Group @ CUED
Levy Processes
Computational and Systems Biology
Uncovering design principles of bacterial biochemical networks and biofilm self-organization
⚠️ Ectopic seminar - N.B. in Biochemistry Department
Machine Learning @ CUED
Nonparametric Bayesian Natural Language Model Domain Adaptation: A Hierarchical, Hierarchical Pitman-Yor Process Language Model
Inference Group
Clustering by linear programming, convex optimization and belief propagation
⚠️ Note unusual time
Machine Learning @ CUED
Bayesian approaches to autonomous Bayesian real-time learning
Machine Learning Reading Group @ CUED
The War on Loops
Machine Learning @ CUED
Non-negative matrix factorization with Gaussian process priors
Machine Learning @ CUED
Matrix Factorization and Relational Learning
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning Journal Club
Machine Learning Book Reading Club
Computational and Systems Biology
MPhil in Computational Biology - Student Project Presentations
Computational and Systems Biology
MPhil in Computational Biology - Student Project Presentations
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning Journal Club
Machine Learning Book Reading Club
Inference Group
Artificial intelligence in combinatorial game design
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning Journal Club
Machine Learning Book Reading Club
Inference Group
From Automated Currency Validation to Protein Fold Recognition: Probabilistic Multi-class Multi-kernel Learning
Machine Learning Journal Club
Machine Learning Book Reading Club
Machine Learning Journal Club
Machine Learning Book Reading Club
SciComp@Cam: Scientific Computing in Cambridge
Provisional: Field Programmable Gate Arrays
⚠️ POSTPHONED TO LATER IN THE YEAR
Inference Group
Modeling with Bounded Partition Functions
Machine Learning @ CUED
Double Feature: Optimal Precoding for MIMO and Divergence Estimation for Continuous Distributions
Machine Learning @ CUED
Nonparametric Bayesian Learning of Switching Dynamical Systems
Machine Learning @ CUED
Message-passing inference on graphical models
Machine Learning Journal Club
Machine Learning book reading club
Microsoft Research Cambridge, general interest public talks
The Geometry of the Space of Shapes
⚠️ Hosted by Prof. Andrew Blake (Microsoft Research)
Machine Learning Journal Club
Machine Learning Book Reading Club
MRC Biostatistics Unit Seminars
Hierarchical Evolutionary Stochastic Search with Adaptive Proposals
Machine Learning Reading Group @ CUED
Variational Bayesian Mixtures of Gaussians
Machine Learning @ CUED
Bayesian analysis of complex biological systems
Microsoft Research Computational Science Seminars
Modelling and simulation of biological systems with COPASI
MRC Biostatistics Unit Seminars
Epidemiological models for a Respondent Driven Sample
SciComp@Cam: Scientific Computing in Cambridge
Provisional: Workflow processing
Disease Ontologies and Information (EBI, Hinxton, 19th June 2008)
Mouse Genome Informatics Database: Phenotypes and Phenotype Ontology
Disease Ontologies and Information (EBI, Hinxton, 19th June 2008)
Towards an Open Source Disease Ontology
⚠️ http://diseaseontology.sf.net/
Disease Ontologies and Information (EBI, Hinxton, 19th June 2008)
The OBO Foundry and PATO
Disease Ontologies and Information (EBI, Hinxton, 19th June 2008)
Ontologies for Biologists – The Promise and the Reality
Disease Ontologies and Information (EBI, Hinxton, 19th June 2008)
Wellcome and Background to Meeting
Disease Ontologies and Information (EBI, Hinxton, 19th June 2008)
Registration and Tea/Coffee
MRC Biostatistics Unit Seminars
A parametric approach to modeling changes in general health and cognition: developing a stochastic model of aging
Inference Group
Bayesian Models for Dependency Parsing Using Pitman-Yor Priors
Machine Learning @ CUED
Variational inference for partially observed diffusion processes
Machine Learning @ CUED
Assessing high-dimensional latent variable models
MRC Biostatistics Unit Seminars
Structure Ranking and System Identification for Non-Linear Biochemical Process Models: Inferring the Structure of the ERK Pathway via Bayes Factors
Machine Learning Journal Club
Cutting Cheese
MRC Biostatistics Unit Seminars
Focussed model selection and model averaging for the Cox regression model
Machine Learning Journal Club
Uniform sampling from various sets
Machine Learning @ CUED
Identification of dynamical subpopulations, optimal experiment design and more
Inference Group
Gaussian Process Density Sampler
Machine Learning Reading Group @ CUED
Stochastic integration and Ito's lemma
Microsoft Research Computational Science Seminars
Structural analysis of cellular networks
Machine Learning @ CUED
H-Infinity Clustering
Machine Learning @ CUED
Sustainable Energy - without the hot air
Machine Learning Journal Club
Journal Club: The Dynamic Hierarchical Dirichlet Process
Statistics
MCMC for doubly-intractable distributions
Machine Learning Reading Group @ CUED
Continuous Time Bayesian Networks
One Day Meeting: Fourth Annual Symposium of the Cambridge Computational Biology Institute
Genomic Regulatory Network Models for Developing Blood Stem Cells
One Day Meeting: Fourth Annual Symposium of the Cambridge Computational Biology Institute
Mapping quantitative traits in mice and plants
One Day Meeting: Fourth Annual Symposium of the Cambridge Computational Biology Institute
Biological learning and memory from a theoretical perspective
One Day Meeting: Fourth Annual Symposium of the Cambridge Computational Biology Institute
Evolution of protein complexes and protein interaction networks
One Day Meeting: Fourth Annual Symposium of the Cambridge Computational Biology Institute
Quantum Mechanical Simulations of Biochemistry
One Day Meeting: Fourth Annual Symposium of the Cambridge Computational Biology Institute
Collective Hydrodynamics of Swimming Micro-Organisms
One Day Meeting: Fourth Annual Symposium of the Cambridge Computational Biology Institute
Signals, Gradients and Cellular Architecture
One Day Meeting: Fourth Annual Symposium of the Cambridge Computational Biology Institute
Determinants of tissue-specific transcriptional regulation in a transplanted chromosome
Bioinformatics joint CRI-BSU series
Novel Methods for Data Integration in Bioinformatics
Statistics
Chance is a Fine Thing
⚠️ Inaugural Lecture as Winton Professor of the Public Understanding of Risk
Machine Learning Journal Club
Object-Attribute Models
SciComp@Cam: Scientific Computing in Cambridge
Provisional: Productivity Applications
Machine Learning @ CUED
Modeling Behaviour in Economic Games using Game-Theoretic POMDPs
Machine Learning @ CUED
Talking with Robots: A Case Study in Architectures for Cognitive Robotics
Machine Learning Journal Club
Measuring Game Temperature With UCT-Monte Carlo
Machine Learning @ CUED
An Introduction to Statistical Learning Theory
⚠️ Machine Learning Tutorial Lecture
Inference Group
Noise in the central nervous system
MRC Biostatistics Unit Seminars
Dynamic predicting by landmarking as an alternative for multi-state modeling: an application to acute lymphoid leukemia data
Machine Learning Journal Club
Tutorial on Monte Carlo methods
Bioinformatics jounal club for the -omics
FlyMine, InterMine and databases for biology.
Microsoft Research Computational Science Seminars
A robustness-based approach to systems-oriented drug design
Inference Group
On Sparsity and Overcompleteness in Image Models
Inference Group
Treed Gaussian Processes for Regression and Classification
⚠️ Note new date and time.
SciComp@Cam: Scientific Computing in Cambridge
Functional Programming
MRC Biostatistics Unit Seminars
Issues and controversies in life course epidemiology
Bioinformatics jounal club for the -omics
Wolfgang Huber from the EBI will be talking on the vsn method.
Machine Learning Journal Club
Expectation Propagation Demonstration
Machine Learning @ CUED
Beam Sampling for Infinite Hidden Markov Models
Microsoft Research Computational Science Seminars
Molecular arms race between host and parasite leads to evolution of robustness against gene loss in signaling networks
Machine Learning @ CUED
Learning quantum physics
Machine Learning Journal Club
Cheap and cheerful neural inference
Machine Learning Journal Club
On the Benefits of Confidence Visualization in Speech Recognition
Statistics
Local and discrete scoring rules
Computational and Systems Biology
A comparison of background correction methods for two-colour microarrays
Inference Group
(clashing event: Sustainable Energy and Arithmetic)
⚠️ Computer Lab seminar clashes with normal group meeting
Machine Learning @ CUED
Convergence analysis of the EM algorithm and joint minimization of free energy
MRC Biostatistics Unit Seminars
New copulae from an order-statistics approach
Machine Learning @ CUED
Discriminative Methods with Structure
Machine Learning Journal Club
Expectation Propagation on the TrueSkill model
Machine Learning Reading Group @ CUED
'All of Nonparametric Statistics'
Machine Learning @ CUED
A Bayesian approach to network modularity: inferring the structure and scale of modular networks
Computational and Systems Biology
tba
Machine Learning Journal Club
Hierarchical Clustering
Bioinformatics jounal club for the -omics
Using biological ontologies in databases: where do GO terms come from?
Machine Learning Reading Group @ CUED
The Information Bottleneck / Dynamic Kernals for speaker verification
Inference Group
How nervous systems are designed to be energy efficient
Microsoft Research Computational Science Seminars
Spatial point process modelling and its applications in ecology
Machine Learning Journal Club
Image superresolution
SciComp@Cam: Scientific Computing in Cambridge
Python Tools for software development
Machine Learning @ CUED
Model selection and model order adaptation for clustering
Machine Learning @ CUED
Expectation Propagation, Experimental Design for the Sparse Linear Model
Computational and Systems Biology
Computational methods to analyse large-scale and high-dimensional gene perturbation screens
Machine Learning @ CUED
Biomedical Image Search
Machine Learning Journal Club
Infera - a Bayesian team-ranking program from 1996
Machine Learning Reading Group @ CUED
Probabilistic Matrix Factorization/Deep Belief Nets
Computational and Systems Biology
A Programming Language for Biology
Inference Group
Bayesian learning of visual chunks by human observers
MRC Biostatistics Unit Seminars
The evolution and adaptation of HIV-1 virulence
MRC Biostatistics Unit Seminars
Bayesian variable selection in generalized linear models under cost constraints
Machine Learning Reading Group @ CUED
Title to be confirmed
Machine Learning @ CUED
Stable distribution and data sketching
Computational and Systems Biology
Open Afternoon for MPhil in Computational Biology
Druggability and the Genome (EBI, Hinxton, 4th February 2008)
Druggable targets - the need for fresh thinking in neglected disease .
Druggability and the Genome (EBI, Hinxton, 4th February 2008)
BindingDB
Druggability and the Genome (EBI, Hinxton, 4th February 2008)
ChEBI: Chemical Entities of Biological Interest
Machine Learning Journal Club
Principled Hybrids of Generative and Discriminative Models
Druggability and the Genome (EBI, Hinxton, 4th February 2008)
DrugBank2
Druggability and the Genome (EBI, Hinxton, 4th February 2008)
ChemoGenomics
Druggability and the Genome (EBI, Hinxton, 4th February 2008)
Introduction and Overview
Machine Learning Reading Group @ CUED
Spectral methods
Computational and Systems Biology
tba
Inference Group
Non-Rigid Photometric Stereo with Colored Lights
Machine Learning @ CUED
Reinforcement Learning
⚠️ Machine Learning Tutorial Lecture (Note unusual day)
Machine Learning Journal Club
Sparse Feature Learning for Deep Belief Networks
Statistics
Identifying Direct and Indirect effects
Bioinformatics jounal club for the -omics
Harnessing naturally randomized transcription to infer regulatory relationships among genes
Machine Learning Reading Group @ CUED
Active Learning
Machine Learning @ CUED
Modeling Science: Topic models of Scientific Journals and Other Large Document Collections
Machine Learning @ CUED
Sparse Gaussian Process in Disease Mapping
Machine Learning Journal Club
Semantic Hashing, Deep Autoencoders and Universal Approximators
Machine Learning Reading Group @ CUED
Bayesian Adaptive Inference and Adaptive Training
Inference Group
NIPS presentations
MRC Biostatistics Unit Seminars
Graphical models for causal reasoning in epidemiology
MRC Biostatistics Unit Seminars
Building Models of Juvenile Salmon Demography
SciComp@Cam: Scientific Computing in Cambridge
Scientific Computing in Cambridge meeting
MRC Biostatistics Unit Seminars
Non-ignorable missing data in parametric survival models
One day Meeting (Cambridge Philosophical Society): Synthetic Biology - Molecular Bioengineering for the 21st Century
General Discussion Session
One day Meeting (Cambridge Philosophical Society): Synthetic Biology - Molecular Bioengineering for the 21st Century
Synthetic biology: from bacteria to stem cells
One day Meeting (Cambridge Philosophical Society): Synthetic Biology - Molecular Bioengineering for the 21st Century
Synthetic Biology: DNA version 2.0
One day Meeting (Cambridge Philosophical Society): Synthetic Biology - Molecular Bioengineering for the 21st Century
Biological Engineering of Plant Systems
One day Meeting (Cambridge Philosophical Society): Synthetic Biology - Molecular Bioengineering for the 21st Century
Exploiting Scaffold Proteins to Generate Diverse I/O Dynamics in MAPK Pathways
One day Meeting (Cambridge Philosophical Society): Synthetic Biology - Molecular Bioengineering for the 21st Century
Towards large-scale integrated nucleic acid logic circuits
One day Meeting (Cambridge Philosophical Society): Synthetic Biology - Molecular Bioengineering for the 21st Century
Computational Design in Synthetic Biology
One day Meeting (Cambridge Philosophical Society): Synthetic Biology - Molecular Bioengineering for the 21st Century
The iGEM competition: Building with biology
One day Meeting (Cambridge Philosophical Society): Synthetic Biology - Molecular Bioengineering for the 21st Century
Tea/ coffee from 9.05 + Introduction (9.30)
Bioinformatics jounal club for the -omics
The use of a power law global error model for the identification of differentially expressed genes in microarray data
Computational and Systems Biology
Title to be confirmed
Inference Group
The development of a motor network in Drosophila, the role of precocious neural activity in the emergence of coordination
Machine Learning @ CUED
Gene Regulatory Network Inference: A Kernel-Based Learning Approach
Machine Learning Journal Club
Reinforcement Learning in continuous state-spaces
Machine Learning Reading Group @ CUED
Hierarchical Dirichlet Processes
Computational and Systems Biology
Complex relationships: modelling epidemics on human social networks
Machine Learning @ CUED
Clinical data based optimal STI strategies for HIV: a reinforcement learning approach
Inference Group
Life beyond the Physics department
SciComp@Cam: Scientific Computing in Cambridge
Scientific Computing in Cambridge meeting
Machine Learning @ CUED
Machine Learning Applications / Challenges in Natural Language Parsing
⚠️ Machine Learning Tutorial Lecture
Machine Learning Reading Group @ CUED
Bayesian Reinforcement Learning
Computational and Systems Biology
Approximate Bayesian Computation and the fossil record
MRC Biostatistics Unit Seminars
Work in progress on the Australian and New Zealand Intensive Care database: I modelling mortality using random effects regression, and II the development of quantitative indices reflecting provider 'process-of-care'
Machine Learning Journal Club
Variational methods
Statistics
Prequential Statistics
Machine Learning Reading Group @ CUED
Transductive and Semi-Supervised Learning
Machine Learning @ CUED
An overview of covariance operators in Hilbert space, and their applications
Machine Learning @ CUED
Optimal Control and Reinforcement Learning with Gaussian Process Models
Machine Learning Journal Club
Loopy Belief Propagation
Machine Learning Reading Group @ CUED
Variational inference and exponential families
Computational and Systems Biology
Title to be confirmed
Inference Group
The last thing that we should talk about
Machine Learning Journal Club
Basics of Belief Propagation
Bioinformatics jounal club for the -omics
A new type of stochastic dependence revealed in gene expression data.
MRC Biostatistics Unit Seminars
What is the deviance information criterion?
Machine Learning Reading Group @ CUED
Sparse Bayesian Linear Models
Computational and Systems Biology
Some questions that can be answered by molecular dynamics
Inference Group
Bliss-Dasher -- Efficient semantic writing with any muscle
SciComp@Cam: Scientific Computing in Cambridge
Scientific Computing in Cambridge meeting
Computational and Systems Biology
Some questions that can be answered by molecular dynamics
Machine Learning @ CUED
Hidden Common Cause Relations in Relational Learning
MRC Biostatistics Unit Seminars
Online inference and prediction for infectious diseases: a case study in Avian Influenza
Machine Learning Journal Club
Fast Visual Tracking By Temporal Consensus
Machine Learning Reading Group @ CUED
Autonomous Agents under Operational Closure
Machine Learning Journal Club
Sensible Priors for Sparse Bayesian Learning
Computational and Systems Biology
Toxicogenomics - helping reshape drug discovery (?)
Machine Learning @ CUED
Optimal Spreading Sequences for Chaos-Based Communication Systems; Using CSK as a Case Study
Bioinformatics jounal club for the -omics
Assessing the probability that a positive report is false: an approach for molecular epidemiology studies.
MRC Biostatistics Unit Seminars
Efficient Bayesian Segmentation of DNA data
Machine Learning Journal Club
Hierarchical Bayesian inference in networks of spiking neurons
Joint EBI/ Cambridge University Research Symposium
Joint EBI/ Cambridge University Research Symposium
SciComp@Cam: Scientific Computing in Cambridge
Scientific Computing in Cambridge meeting
Machine Learning @ CUED
Graph Kernels for Data Mining
Machine Learning Journal Club
Predictive Interaction using the Delphian Desktop
Machine Learning @ CUED
Geometric Algorithms for Linear Independent Component Analysis
Machine Learning @ CUED
Covariate Shift Adaptation: Supervised Learning When Training and Test Inputs Have Different Distributions
Inference Group
Five energy plans for Britain
Genetics Seminar Series
Alternative splicing in the human transcriptome: Functional and structural influence on proteins
⚠️ ECTOPIC SEMINAR
Microsoft Research Machine Learning and Perception Seminars
Physics-Based Human Motion Models for Animation and Tracking
Machine Learning Journal Club
Combining Causal and Similarity-based reasoning
Machine Learning Journal Club
Efficient Bayesian Task-Level Transfer Learning
Bioinformatics jounal club for the -omics
Centering, scaling, and transformations: improving the biological information content of metabolomics data
Inference Group
What is a Fab Lab?
Machine Learning Journal Club
Kingman's coalescent, non-parametric Bayesian agglomerative clustering
SciComp@Cam: Scientific Computing in Cambridge
Scientific Computing in Cambridge meeting
Machine Learning Journal Club
Contextual dependencies in unsupervised word segmentation
Microsoft Research Machine Learning and Perception Seminars
Bayesian network structure learning from uncertain interventions
Machine Learning Journal Club
Pre-Gatsby Workshop
Machine Learning Journal Club
Knowledge Compilation
Bioinformatics jounal club for the -omics
Bootstrapping cluster analysis: assessing the reliability of conclusions
SciComp@Cam: Scientific Computing in Cambridge
Scientific Computing in Cambridge meeting
Machine Learning Journal Club
Clustering by Passing Messages Between Data Points
Machine Learning Journal Club
Title Language Model
Systems Biology
Individual variation identifies evolutionary patterns between species
⚠️ Population and Evolutionary Approaches to Biological Systems 1 Day Symposium
Systems Biology
Worldwide distribution of human genetic diversity
⚠️ Population and Evolutionary Approaches to Biological Systems 1 Day Symposium
Systems Biology
Worldwide distribution of human phenotypic diversity
⚠️ Population and Evolutionary Approaches to Biological Systems 1 Day Symposium
Systems Biology
The systems biology of influenza
⚠️ Population and Evolutionary Approaches to Biological Systems 1 Day Symposium
Systems Biology
Disease dynamics at different scales
⚠️ Population and Evolutionary Approaches to Biological Systems 1 Day Symposium
Systems Biology
Evolving mechanisms of pattern formation: Segmentation in arthropods
⚠️ Population and Evolutionary Approaches to Biological Systems 1 Day Symposium
Systems Biology
Developmental and evolutionary dynamics of the gap gene system.
⚠️ Population and Evolutionary Approaches to Biological Systems 1 Day Symposium
Systems Biology
Disease in a changing landscape
⚠️ Population and Evolutionary Approaches to Biological Systems 1 Day Symposium
Systems Biology
A systems approach to understand the condition dependency of genetic interactions
⚠️ Population and Evolutionary Approaches to Biological Systems 1 Day Symposium
Systems Biology
Genomic approaches to speciation and fitness: old wines in new bottles
⚠️ population and Evolutionary Approaches to Biological Systems 1 Day Symposium
MRC Biostatistics Unit Seminars
Graphical Data and Data Graphics in R
MRC Biostatistics Unit Seminars
Identifying true positive associations in genome-wide association studies
MRC Biostatistics Unit Seminars
The Reporting of Associations in Genome-Wide Studies
Machine Learning Journal Club
Bring your Papers!
Computational and Systems Biology
Computational genomics of structural RNAs
⚠️ CCBI Distinguished Seminar Series
Machine Learning Reading Group @ CUED
Kingman's coalescent, non-parametric Bayesian agglomerative clustering, and ICML 2007
Machine Learning Reading Group @ CUED
Sensible priors from finite linear models
⚠️ Note unusual time
Microsoft Research Machine Learning and Perception Seminars
Generative models for audio and music processing
SciComp@Cam: Scientific Computing in Cambridge
Report from Apple WWDC07
SciComp@Cam: Scientific Computing in Cambridge
Linux on the Playstation3
Machine Learning Reading Group @ CUED
Statistical Models for Partial Membership
Symposium on Computational Biology
DNA-binding computation at large and small scales
Symposium on Computational Biology
Insight into ion channel biophysics via computer simulations
Symposium on Computational Biology
Quadruple stranded DNA: cancer, gene regulation and evolution
Symposium on Computational Biology
Simulations of phase transitions: from colloids to proteins
Symposium on Computational Biology
The physics of protein folding
Symposium on Computational Biology
Measuring and predicting complexity
Machine Learning Reading Group @ CUED
Infinite ICA and Information Retrieval
Inference Group
Language Modelling Discussion
Inference Group
Open Vocabulary Confusion Networks for Speech Recognition
Microsoft Research Machine Learning and Perception Seminars
identity variables for face recognition: from distance based methods to probabilistic inference
MRC Biostatistics Unit Seminars
Inference for binary Markov random fields without tears (or MCMC).
Machine Learning Reading Group @ CUED
Overlapping Clusters and 4th-year Projects
Inference Group
An Error-Correcting Keyboard
Inference Group
Probabilities, Complexities and Game Semantics
Machine Learning Reading Group @ CUED
What can Gaussian Processes do for Reinforcement Learning?
One Day Meeting - Third Annual Symposium of the Cambridge Computational Biology Institute
A human protein atlas
⚠️ Registration required via http://www.ccbi.cam.ac.uk/Events/Workshops/symp_07.php
One Day Meeting - Third Annual Symposium of the Cambridge Computational Biology Institute
The biology of common disease from a genome-wide perspective: susceptibility genes as nodes for pathways and systems
⚠️ Registration required via http://www.ccbi.cam.ac.uk/Events/Workshops/symp_07.php
One Day Meeting - Third Annual Symposium of the Cambridge Computational Biology Institute
Genome regulation: a sequence-gazer's view.
⚠️ Registration required via http://www.ccbi.cam.ac.uk/Events/Workshops/symp_07.php
One Day Meeting - Third Annual Symposium of the Cambridge Computational Biology Institute
Learning from the worm: predicting phenotype from genotype
⚠️ Registration required via http://www.ccbi.cam.ac.uk/Events/Workshops/symp_07.php
One Day Meeting - Third Annual Symposium of the Cambridge Computational Biology Institute
Lies, damn lies and metabolomics - statistical approaches for processing metabolomic data.
⚠️ Registration required via http://www.ccbi.cam.ac.uk/Events/Workshops/symp_07.php
One Day Meeting - Third Annual Symposium of the Cambridge Computational Biology Institute
Oscillators and sychronisation in circadian rhythms
⚠️ Registration required via http://www.ccbi.cam.ac.uk/Events/Workshops/symp_07.php
One Day Meeting - Third Annual Symposium of the Cambridge Computational Biology Institute
Epidemics on Networks
⚠️ Registration required via http://www.ccbi.cam.ac.uk/Events/Workshops/symp_07.php
One Day Meeting - Third Annual Symposium of the Cambridge Computational Biology Institute
Modelling the hidden world of protein activities
⚠️ Registration required via http://www.ccbi.cam.ac.uk/Events/Workshops/symp_07.php
MRC Biostatistics Unit Seminars
Representing uncertainty in numerical climate models
Machine Learning Reading Group @ CUED
System Conditioning vs Explicit Bayes Inference, and Collaborative LDA
Inference Group
Learning and Stability in Random Sigma-Pi Networks
Machine Learning Reading Group @ CUED
Affinity Propagation and Hierarchical Beta Processes
⚠️ Room changed, Note unusual time
Inference Group
Shape writing: fluid text entry on mobile devices
Machine Learning Reading Group @ CUED
Optimal Learning
Inference Group
Bayesian nonparametric latent feature models
Machine Learning Reading Group @ CUED
Gaussian Approximations for Binary Gaussian Process Classification, and Hidden Topic Markov Models
Inference Group
Context Tree Weighting
Machine Learning Reading Group @ CUED
Function Approximation in MDPs
MRC Biostatistics Unit Seminars
Joint modelling of competing risks of drug withdrawal and quality of life in epilepsy trials.
Machine Learning Reading Group @ CUED
Change Point Problems in Linear Dynamical Systems
⚠️ Postponed (originally April 5)
Microsoft Research Machine Learning and Perception Seminars
A Bayesian model that links microarray mRNA measurements to mass spectrometry protein measurements
Probabilistic Systems, Information, and Inference Group Seminars
Analysis of Channel Coding for Redundant Sources
Machine Learning Reading Group @ CUED
GP-LVMs
Inference Group
Inductive Logic Programming and Kernel methods
MRC Biostatistics Unit Seminars
Models for baseline and treatment effects in meta-analysis
Inference Group
Logistic regression with a Laplacian prior on the singular values: convex duality and application to EEG classification.
⚠️ Note unusual time and location
Machine Learning Reading Group @ CUED
Topics in Convex Optimisation
Inference Group
Monte Carlo Approaches to Game Playing
Microsoft Research Machine Learning and Perception Seminars
Motion Tracking
Machine Learning @ CUED
Logistic Regression with a Laplacian prior on the Eigenvalues: Convex duality and application to EEG classification
⚠️ Note different room and time
Microsoft Research Machine Learning and Perception Seminars
A complete set of rotationally and translationally invariant features based on a generalization of the bispectrum to non-commutative groups
Inference Group
Gaussian Process Product Models
Computational and Systems Biology
Automated image analysis for high-throughput cell-based microscopy assays with R and Bioconductor
Microsoft Research Machine Learning and Perception Seminars
Reverse Engineering the Human Visual System with Networks of Spiking Neurons
Machine Learning Reading Group @ CUED
An Introduction to Generalized Ensemble MCMC for Machine Learning
Computational and Systems Biology
Open Afternoon for MPhil in Computational Biology
Inference Group
Metropolis-Coupled MCMC for Nested Sampling
Machine Learning Journal Club
Journal Club: "Analysis of Contour Motions"
Machine Learning @ CUED
Dirichlet Processes and Hierarchical Dirichlet Processes
⚠️ Advanced Machine Learning Tutorial Lecture
Machine Learning Reading Group @ CUED
Some NIPS papers
Computational and Systems Biology
The FlyMine/ InterMine Project
Inference Group
Some interesting data: Cryptic DNA sequence periodicities are ubiquitous, organism specific and distinguish introns from exons.
Machine Learning @ CUED
An Introduction to Non-parametric Bayesian Methods
⚠️ Room changed this week!
Machine Learning Reading Group @ CUED
Universal Artificial Intelligence, and Probability Monads
Computational and Systems Biology
Modelling Epidemics
MRC Biostatistics Unit Seminars
Bayesian inference for stochastic epidemic models in structured populations based on final outcome data
Machine Learning Reading Group @ CUED
Neural Networks
Computational and Systems Biology
Monkeys on Trees: A Bayesian Approach to Inferring Primate Divergence Times
Inference Group
NIPS presentations
Machine Learning Journal Club
Journal Club: "Bayesian Policy Gradient Algorithms"
Microsoft Research Machine Learning and Perception Seminars
Margin- and Evidence-Based Approaches for EEG Signal Classification
Machine Learning Reading Group @ CUED
Latent Dirichlet Allocation and Dirichlet Diffusion Trees
Computational and Systems Biology
Identifying novel therapies for breast cancer using Independent Component Analysis
Machine Learning Journal Club
Gaussian Process Belief Propagation
Machine Learning @ CUED
Robot Localisation and Mapping
⚠️ Advanced Machine Learning Tutorial Lecture
Machine Learning Reading Group @ CUED
Non-parametric mixture models
Computational and Systems Biology
Identifying deletions and duplications from PCR data
⚠️ All welcome and please feel free to join us for coffee and biscuits after the talk in the Pavilion G common room
Computational and Systems Biology
"Identifying deletions and duplications from PCR data"
⚠️ This talk has been canceled/deleted
Machine Learning Journal Club
Loss Functions for Discriminative Training of Energy-Based Models
Inference Group
Modeling text with Dirichlet compound multinomial distributions
Machine Learning Journal Club
Estimation of non-normalized statistical models using score matching
Machine Learning Reading Group @ CUED
Collaborative Filtering
Inference Group
Learning from positive and unlabeled data
Computational and Systems Biology
Protein structure determination using NMR chemical shifts
MRC Biostatistics Unit Seminars
Medical statistics: A little bit of history
Inference Group
HMMs for controlling dynamical systems
Microsoft Research Machine Learning and Perception Seminars
Computer Go Research in the University of Alberta GAMES Group
Inference Group
Robust Gaussian Process Regression and Applications
Microsoft Research Machine Learning and Perception Seminars
Where’s my rocket? – Stochastic simulations of rocket flight paths
Machine Learning Journal Club
Journal Club: "Reducing the Dimensionality of Data with Neural Networks"
Inference Group
Transcription regulation: from parts list to genomic network.
Machine Learning Reading Group @ CUED
On Choosing Priors
Microsoft Research Machine Learning and Perception Seminars
Learning Conditional Random Fields with Hierarchical Features: Application to the Game of Go
Computational and Systems Biology
Machine Learning Methods for Uncovering cis-Regulatory Modules
Microsoft Research Machine Learning and Perception Seminars
Constraint Programming Techniques for Virtual Camera Control
Machine Learning Journal Club
Journal Club: "Clustering appearance and shape by learning jigsaws"
Machine Learning Reading Group @ CUED
Partially Observable Markov Decision Processes (POMDPs)
Computational and Systems Biology
Genome Informatics at the Sanger Institute
Inference Group
Bayesian estimation of neuronal connectivity from MEA recordings
Machine Learning Journal Club
Journal Club "Searching for memories, Sudoku, implicit check-bits, and the iterative use of not-always-correct rapid neural computation"
Machine Learning Reading Group @ CUED
Nonlinear Dimensionality Reduction
Inference Group
Vector Gaussian Processes
Computational and Systems Biology
Microarrays and molecular biology: beyond gene expression profiling
Machine Learning Journal Club
Journal Club: "Document language models, query models, and risk minimization for information retrieval"
Machine Learning Reading Group @ CUED
Machine Learning Reading Group in Engineering Department
Inference Group
Do Scanning Electron Microscopes have a point-spread function?
Microsoft Research Machine Learning and Perception Seminars
Learning microRNA regulatory networks from genomic sequence and expression data
Machine Learning Journal Club
Journal Club: A Neural Probabilistic Language Model
Computational and Systems Biology
Cell signalling and oscillations
Computational and Systems Biology
*ectopic seminar* Evidence for the existence of organism-specific regulatory elements that are linked to RNAi
⚠️ * Ectopic Seminar at Genetics Department *
Machine Learning @ CUED
Gaussian Processes for Machine Learning
⚠️ Advanced Machine Learning Tutorial Lecture
Inference Group
Dynamic imaging of blood flow in the conjunctival and episcleral microcirculations of the human eye: a new chapter in diagnostic imaging?
Computational and Systems Biology
Evolution and dynamics of transcription factor repertoires
Machine Learning Journal Club
Expectation Consistent Approximate Inference
Computational and Systems Biology
Linear Separability of Gene Expression Dataset
Inference Group
Teaching Statistics - A Bag of Tricks
Inference Group
Leaf Selection for Maximising Diversity in a Tree
Computational and Systems Biology
DESCRIBING DRUG TOXICITY USING FUNCTIONAL DATA ANALYSIS AND THE MODEL-DRIVEN CLUSTERING OF GENE EXPRESSION BIOMARKERS. (HOW TO TURN YOUR MPHIL INTO A PAYCHEQUE)
Computational and Systems Biology
High resolution models of genome regulatory events
⚠️ This lecture is part of the Distinguished Seminar Series run by the CCBI.
Machine Learning @ CUED
Mixture Models and the EM Algorithm
⚠️ Advanced Machine Learning Tutorial Lecture
Inference Group
Optimised Digital Fountain Codes for Medium Blocklengths
Inference Group
An interesting preprint
Computational and Systems Biology
Describing drug toxicity using functional data analysis and the model-driven clustering of gene-expression bio-markers
Inference Group
MCMC for doubly-intractable distributions
Machine Learning Journal Club
A Hierarchical Bayesian Language Model based on Pitman-Yor Processes
Inference Group
How to veto anonymously under surveillance?
Machine Learning Journal Club
Journal Club: "A Bayesian Analysis of Projective Incidence"
Inference Group
Naive OCR?
Inference Group
Cognitive Cars
Inference Group
neural phase codes
Inference Group
Graphical Combinator Programming
Inference Group
The Manufacture of Bioethanol - A brief Introduction
Inference Group
Divergence measures and latent variable models
Inference Group
Implicit learning in Music
Inference Group
On the Analysis of Ellipsoid Approximation of Nested Sampling
Inference Group
Gaussian Process models for solving ODEs
Computer Modelling in Biology
Ligand detection and discrimination by spatial relocalisation: the complexities of T cell activation
Inference Group
Music Access for the Disabled
Inference Group
Blissymbolics - The Emergence of a Written Language
Inference Group
In search of the brain's wiring
Inference Group
A Bayesian Unfolding Method Applied to the PAMELA Experiment
Inference Group
Blissymbolics
Machine Learning Journal Club
Journal Club: Dirty paper coding and applications
Inference Group
Finite element modelling of growing microtubules
Machine Learning Journal Club
Bayesian Sets
Machine Learning Journal Club
SUPERFAST SOLUTION OF REAL POSITIVE DEFINITE TOEPLITZ SYSTEMS
Inference Group
Title to be confirmed
Computational and Systems Biology
CCBI 2nd Annual Symposium
Machine Learning Journal Club
Unsupervised Learning from Users' Error Correction in Speech Dictation
Machine Learning Journal Club
Hierarchical Bayesian inference in the visual cortex
Inference Group
How to Parameterize a Positive-definite Matrix
Inference Group
To be confirmed
Inference Group
The Capacity of the Deletion Channel
Machine Learning Journal Club
"Weak pairwise correlations imply strongly correlated network states in a neural population"
Machine Learning Journal Club
Machine Learning Journal Club: Gaussian Processes for Machine Learning Chapter VIII
Inference Group
Bayesian approximation for physical inverse problems
Inference Group
Hierarchical Passage Retrieval
Machine Learning Journal Club
Machine Learning Journal Club: "Gaussian Processes for Machine Learning"
Inference Group
Bayesian Online Changepoint Detection
Machine Learning Journal Club
Machine Learning Journal Club: "Gaussian Processes for Machine Learning"
Inference Group
Epitomic representation of natural signals
Machine Learning Journal Club
Machine Learning Journal Club: "Gaussian Processes for Machine Learning"
Inference Group
Aggregation of Particles in Stochastic Flows
Inference Group
Student Project Presentations: "Colour Memorisation", "One button communication" and "Optimising digital fountain codes"
Computational and Systems Biology
Phase transitions in biopolymers: statistical mechanics of interacting loops
Machine Learning @ CUED
Probabilistic Dimensional Reduction with the Gaussian Process Latent Variable Model
Inference Group
Speech Recognition During Dictation Corrections
Computational and Systems Biology
Modelling equine influenza
Machine Learning Journal Club
Machine Learning Journal Club: "Dependent Gaussian Processes"
Inference Group
Topic Modeling: Beyond Bag-of-Words
Computational and Systems Biology
To be confirmed
Inference Group
Uncertainty Logic
Machine Learning Journal Club
Machine Learning Journal Club: "Assessing Approximations for Gaussian Process Classification"
Inference Group
Experimental Annotation of the Human Genome
Computational and Systems Biology
To be confirmed
Machine Learning Journal Club
Machine Learning Journal Club: "Sparse Gaussian Processes using Pseudo-inputs"
Inference Group
Virtual-move Parallel Tempering
Computational and Systems Biology
Disease in a changing landscape
Machine Learning Journal Club
reading-group: Divergence measures and message passing
Inference Group
Latency-optimal fault-tolerant replication
Computational and Systems Biology
TBC
Machine Learning Journal Club
reading-group: Expectation Propagation
Inference Group
Dynamical Networks for Agent Systems
Computational and Systems Biology
Mathematical Models of Tumour Dormancy
Inference Group
Recognition and prediction of biological motion
Machine Learning Journal Club
reading-group: Interpolating Between Types and Tokens by Estimating Power-Law Generators
Inference Group
Eye Tracking with Consumer Hardware
Machine Learning Journal Club
reading-group: TD-Gammon
Inference Group
Cheap and cheerful inference machines for tracking
Machine Learning Journal Club
Reading Group: "Learning to Predict by the Methods of Temporal Differences"
Inference Group
Efficient Quantum Computation with linear optics
Inference Group
Locked-in syndrome
Inference Group
Monte Carlo is Bayesian
Inference Group
Dasher for the blind, and some visual illusions
Inference Group
A Cross-Entropy Based Method to Analyse Iterative Decoding
Inference Group
Bayesian Pattern Ranking for Move Prediction in the Game of Go
Inference Group
Adaptive Monte Carlo Methods for Simulation and Optimization
Inference Group
Language relationships, phonology, and Greek
Inference Group
Efficient communication with buttons: an update on Button Dasher
Inference Group
Progress with #Dasher, a Continuous Gesture IDE
Inference Group
Why do fruitflies like bananas?
Machine Learning Journal Club
multicanonical sampling
Inference Group
An introduction to Brain-Computer Interfaces
Inference Group
To be confirmed
Inference Group
LOCUS: Learning Object Classes with Unsupervised Segmentation
Inference Group
Efficient computer interfaces using continuous gestures, language models, and speech; Probabilistic methods for interpreting electronic ink
Inference Group
A Fast Learning Algorithm for Deep Belief Nets
Inference Group
Epitomes And Epitexts
Inference Group
Monte Carlo experiments in computer Go
Inference Group
Language Modelling In Dasher: A Tutorial
Inference Group
Hierarchical Dirichlet Process Models for Time Series Data
Machine Learning Journal Club
Reading group: Bayesian inference via search
Inference Group
Japanese Language Model
Inference Group
A Tale of T9
Inference Group
Information and Intelligence
Inference Group
Neighbourhood Components Analysis
Inference Group
Nested Sampling for Motif Discovery
Inference Group
Joint Gaussian Process-Density Mixtures
Inference Group
Computer Othello
Inference Group
Variational Gibbs Sampling
Inference Group
Astronomical Image Recognition
Inference Group
Bloom Filters and Tries (a comparison)
Inference Group
The predictive power of contractive neural-network spaces
Inference Group
Bayesian Learning for Visual Inference
Inference Group
Approximating The Hierarchical Dirichelet Distribution
Please see above for contact details for this list.