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Changmin Yu.
Thursday 26 March 2026, 09:00-11:00
CBL important
Description to be confirmed
Contact: dw304
0 upcoming talks View 813 archived talks
Computational Neuroscience
Hippocampal neuronal activity is aligned with action plans
Computational Neuroscience
Multiplexed representations of decision content and uncertainty in visual processin
Computational Neuroscience
Compositional Generalization and Learning
Computational Neuroscience
Mind-body dualism: A perceptual core
Computational Neuroscience
Infinite Hidden Semi-Markov Models
Computational Neuroscience
Frugal computation
Computational Neuroscience
Tiny & Gigantic Neural Networks
Computational Neuroscience
Lazy-rich learning
Computational Neuroscience
Lazy-rich learning
Computational Neuroscience
Neural basis of decision making
Computational Neuroscience
From Data to Models to Understanding: Evaluating Neural Latents and Finding Decision Boundaries in Recurrent Neural Networks (RNNs)
Computational Neuroscience
Thalamocortical Interactions for Flexible Cognition
Computational Neuroscience
Cerebellum Computation
Computational Neuroscience
The Fruit Fly Connectome and Beyond
Computational Neuroscience
Multitasking and compositionality in brain and in neural networks
Computational Neuroscience
Context, Computation, and Continuity: Neural Mechanisms of Memory and Decision-Making
Computational Neuroscience
Context, Computation, and Continuity: Neural Mechanisms of Memory and Decision-Making
Computational Neuroscience
Discovering reward-guided learning strategies from large-scale datasets
Computational Neuroscience
Dendrites, Synaptic Plasticity and Hippocampal Place Fieldsβ
Computational Neuroscience
Connectome-based Echo State Networks
Computational Neuroscience
Quantifying individuality in neural circuit representations
Computational Neuroscience
The successor representation, its neural substrate, and behavioural consequences.
Computational Neuroscience
In-Context Learning
Computational Neuroscience
Integrating Random Memory Patterns and Spatial Maps in Food-Caching Birds
Computational Neuroscience
The Continual Learning (CL) Theory
Computational Neuroscience
Hopfield Networks: From Neuroscience to Machine Learning and Back
Computational Neuroscience
Certain about uncertainty? Latent representations of VAEs optimized for visual tasks.
Computational Neuroscience
Neural circuit reorganisation and functional resilience
Computational Neuroscience
Inverse normative modeling of continuous perception and action
Computational Neuroscience
Data-driven models of neural and behavioural learning
Computational Neuroscience
Evaluating dynamical systems hypotheses for pattern generation in motor cortex
Computational Neuroscience
Modelling C. elegans pharynx
Computational Neuroscience
Relating the diversity of firing rates to the dimension of variability in recurrent networks
Computational Neuroscience
State space models (as alternatives to Transformers)
Computational Neuroscience
Geometry of neural representations
Computational Neuroscience
Sensory prediction errors in thalamocortical circuits
Computational Neuroscience
Geometry of population coding in large and transcriptomically-identified cortical populations
Computational Neuroscience
Causal inference during motion perception, and its neural basis
Computational Neuroscience
Learning Bayesian inference models of cortical visual processing
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
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Circuit for memory-based action selection
Computational Neuroscience
Integrated Spin model with global inhibition for decision making
Computational Neuroscience
Unifying the mechanisms of the hippocampal and prefrontal cognitive maps
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Neurotransmitter receptor gradients: gateways for subcortical routing of cortex-wide dynamics during cognition
Computational Neuroscience
Behavioral, Neuropsychological, and Computational Perspectives on Sensorimotor Learning
Computational Neuroscience
Behavioral, Neuropsychological, and Computational Perspectives on Sensorimotor Learning
Computational Neuroscience
Title to be confirmed
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Consistent Validation for Predictive Methods in Spatial Settings
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Modern Bayesian Experimental Design
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
A new look at eye design
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Structured recognition for generative models with explaining away
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
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Convergence bounds for the Random Walk Metropolis algorithm - Perspectives from Isoperimetry
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
The unbreakable lightness of single neuron non-linearities in learning
Machine Learning @ CUED
Calls to F the Algorithm: Lessons from the 2020 Exam Debacle
Machine Learning @ CUED
Scalable simulation and inference in non-Gaussian stochastic PDEs
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Understanding the emergence of neural population dynamics underlying behaviour
Machine Learning @ CUED
Measuring Alignment Between Perceptual Systems: An Analysis Through The Lens of Shared Invariances
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Gaussian processes, spectral analysis kernels and optimal transport
Machine Learning @ CUED
Deep Reinforcement Learning for Multi-Agent Interaction
Machine Learning @ CUED
Presenting Hawk-Eyeβs 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
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Random walks, self-reinforcement and neurons
Machine Learning @ CUED
Noise-Aware Differentially Private Synthetic Data
Machine Learning @ CUED
Estimating RSV seasonality from pandemic disruptions: a modelling study
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
How a recurrent circuit of Poisson spiking neurons is able to implement sampling-based inference
Machine Learning @ CUED
Beyond Conformal Prediction: Distribution-Free Uncertainty Quantification for Complex Machine Learning Tasks
Machine Learning @ CUED
Graph neural network approach for decentralized multi-robot coordination
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Connectivity inference in visual cortex and characterization of contrast-suppressed cells
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Capacity and errors in classification of object manifolds
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
A theory for Hebbian Learning in recurrent E-I networks
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
The covariance perceptron: Theory and application to reservoir computing
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Cognitive switches and functional reprogramming of sensory cortex
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Efficient and Structured Uncertainty: Challenges and Opportunities
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Why do neurons spike spontaneously?
Computational Neuroscience
Why do neurons spike spontaneously?
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Game Playing Meets Game Theory: Strategic Learning from Simulated Play
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Robust Deep Learning Under Distribution Shift
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Structure in the randomness of trained recurrent neural networks
Machine Learning @ CUED
Models and inference for temporal Gaussian processes
Computational Neuroscience
Computational neuroscience journal club
Computational Neuroscience
Neural information processing during behavior and sleep
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
Machine Learning @ CUED
Explaining Neural Networks: Post-hoc and Natural Language Explanations
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Dopamine as prediction error in active inference
Computational Neuroscience
Neurotransmitter spillover modulates neuronal information transmission
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Learning-Algorithms from Bayesian Principles
Computational Neuroscience
Wearable non-invasive human neural interface with action potential resolution
Computational Neuroscience
Wearable non-invasive human neural interface with action potential resolution
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
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Information Consumption on Social Media: Efficiency, Trust, and Divisiveness
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
How perception informs urgent saccadic choices: halting, acceleration, and deceleration
Machine Learning @ CUED
Why Do We Need New Hardware & Software for Machine Intelligence?
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Nonparametric Generative Modeling via Optimal Transport and Diffusions with Provable Guarantees
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
NeVAE: A Deep Generative Model for Molecular Graphs
Machine Learning @ CUED
Global model explainability via aggregation
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Robust machine learning for causal inference in health care
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
The K-FAC method for neural network optimization
Computational Neuroscience
Stimulus complexity shapes response correlations in primary visual cortex
Machine Learning Reading Group @ CUED
Generative models for few-shot prediction tasks
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Neural circuit mechanisms of learning and attentional task-switching during visually-guided behaviour in mice
Machine Learning @ CUED
Online Meta-Learning
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
High-dimensional dynamics of generalization error in neural networks: implications for experience replay
Machine Learning @ CUED
Gauge Equivariant Convolutional Networks on Manifolds
Machine Learning @ CUED
Observation and Intervention Incentives in Causal Influence Diagrams: Towards an Understanding of Powerful Machine Learning Systems
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Local and global synaptic credit assignment
Machine Learning @ CUED
Fairness for Sequential Decision Making Algorithms
Machine Learning @ CUED
Gaussian processes for inferring latent functions in complex data models
Computational Neuroscience
Computational Neuroscience Journal Club
Adrian Seminars in Neuroscience
Adrian Seminar - "Computational model of rapid learning in hippocampus".
Computational Neuroscience
A brain-machine interface for locomotion driven by subspace dynamics
Computational Neuroscience
Neural mechanisms of model-based planning in the rat
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Causal Inference for Treatment Effects: A Theory and Associated Learning Algorithms
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Reactivation in biological and artificial neural networks
Machine Learning @ CUED
Interpretability - the myth, questions, and some answers
Machine Learning @ CUED
Constraint-based causal Discovery from NOnstationary/heterogeneous Data (CD-NOD)
Computational Neuroscience
Computational Neuroscience Journal Club
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
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Structured deep models: Deep learning on graphs and beyond
Machine Learning @ CUED
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Semi-Generative Modelling: Domain Adaptation with Cause and Effect Features
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Algorithmic Glass Ceiling in Social Networks
Computational Neuroscience
Information Efficacy of a Dynamic Synapse
Machine Learning @ CUED
A Bayesian Perspective on Generalization and SGD
Machine Learning @ CUED
Algorithmic Glass Ceiling in Social Networks
Machine Learning @ CUED
Structure in tensor-variate data: a trivial byproduct of simpler phenomena?
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Lipschitz Global Optimization
Computational Neuroscience
Interfacing with the brain using organic electronics
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Variational inference for some models with Polya-Gamma latent variables and Gaussian process priors
Machine Learning @ CUED
Bayesian Generative Adversarial Networks
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
AI for Inclusive Finance
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Backprop through the Void: Optimizing Control Variates for Black-Box Gradient Estimation.
Machine Learning @ CUED
Learning to Learn without Gradient Descent by Gradient Descent
Machine Learning @ CUED
Towards true end-to-end learning & optimization
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
How much to gain: Controlling space and time via gain modulation in cortical networks
Machine Learning @ CUED
Targeted Disclosure to Support Auditing and Accountability for Automated Decision-making
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Somatosensory cortex is essential for adaptive motor control in mice
Computational Neuroscience
From the olfactory cocktail party to markerless tracking
Machine Learning @ CUED
Nonlinear ICA using temporal structure: a principled framework for unsupervised deep learning
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Spike timing in motor control
Machine Learning @ CUED
Transfer Learning for NLP
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
A Bayesian Treatment for Uncertainty -- and its application in health care
Machine Learning @ CUED
Unbiased Estimation of the Eigenvalues of Large Implicit Matrices
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
Machine Learning @ CUED
Understanding Black-box Predictions via Influence Functions
Computational Neuroscience
Computational Neuroscience Journal Club
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
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
motifNet: Deep learning for system identification of regulatory networks
Computational Neuroscience
Neural network models of free recall and spatial navigation
Computational Neuroscience
Inferring decision rules from evidence, choice, and reaction times
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
On Different Distances Between Distributions and Generative Adversarial Networks
Computational Neuroscience
Computational Neuroscience Journal Club
Adrian Seminars in Neuroscience
Decoding the population activity of grid cells for spatial localization and goal-directed navigation
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning Study Group
Deep Learning Book - Meeting 9 - Representation Learning
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning Study Group
Deep Learning Book - Meeting 8 - Autoencoders
Machine Learning Study Group
Deep Learning Book - Meeting 7 - Neural Turing Machines & Conditional Random Fields as RNNs
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
Computational and Biological Learning Seminar Series
Control, inference and learning
Machine Learning @ CUED
Differential Privacy Tutorial
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning Study Group
Deep Learning Book - Meeting 5 - ResNets and DenseNets
Machine Learning @ CUED
Cooperative Inverse Reinforcement Learning
Machine Learning Study Group
Deep Learning Book - Meeting 4 - Convolutional Networks
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Dynamic reorganization of neuronal activity patterns in parietal cortex
Machine Learning Study Group
Deep Learning Book - Meeting 3 - Optimization
Machine Learning @ CUED
Bayesian optimisation in many dimensions with bespoke probabilistic programs
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning Study Group
Deep Learning Book - Meeting 2 - Regularization
Machine Learning Study Group
Deep Learning Book - Meeting 1 - Deep Feedforward NNs
Machine Learning @ CUED
Variational Bayes In Private Settings
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Julia: Introduction and new developments
Computational Neuroscience
Computational Neuroscience Journal Club
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
Machine Learning @ CUED
Variational autoencoders with latent graphical models
Machine Learning @ CUED
Learning with limited supervision
Machine Learning @ CUED
A tale of P-matrices and TripleSpinners - the unreasonable effectiveness of structured models in nonlinear embeddings
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Rejection Sampling Variational Inference
Computational Neuroscience
Neural representations of uncertainty: the right tool for the right job
Machine Learning @ CUED
Probabilistic Numerical Computation: A New Concept?
Computational Neuroscience
Prospective coding by spiking neurons
Computational Neuroscience
Grid cells get back to the memory game
Computational Neuroscience
Computational Neuroscience Journal Club
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.
β οΈ Note venue: James Dyson Building
Machine Learning @ CUED
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models
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
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Moment matching for latent variable models: from ICA to LDA and CCA
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Multiresolution Matrix Factorization
Machine Learning @ CUED
Dynamic Models for Health Data
Machine Learning @ CUED
Learning with Memory Embeddings
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Data Driven Discrete Time Modeling of Continuous Time Nonlinear Systems: Problems, Challenges, Success Stories
Computational Neuroscience
Computational Neuroscience Journal Club
Computational and Biological Learning Seminar Series
Internal models and the neural control of prey interception
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
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Scaling and Generalizing Approximate Bayesian Inference
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
A decision-theoretic framework for active cognition
Computational Neuroscience
Computational Neuroscience Journal Club
arg58's list
A modular architecture for Unicode text compression
Machine Learning @ CUED
Modeling the Dynamics of Online Learning Activity
Machine Learning @ CUED
Developments in Exact Inference in Graphical Models
Machine Learning @ CUED
Approximation strategies for structure learning in Bayesian networks
β οΈ Note: via Skype!
Machine Learning @ CUED
Automated Reasoning and AI for Large Formal Mathematics
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
Computational Neuroscience
Perceptual decision-making: models of the decision-making process and formulation of uncertainty
Computational Neuroscience
Towards a theory of layered neural circuit architectures
Machine Learning @ CUED
Towards Weaker Supervision and Simpler Pipelines in Speech Recognition
Machine Learning @ CUED
Sum-Product Networks for Probabilistic Modeling
Craik Club
Perception as a closed-loop convergence process
β οΈ The host for this talk is MΓ‘tΓ© Lengyel. Note the unusual time and the unusual location
Machine Learning @ CUED
MLE-Struct: Bethe Learning of Graphical Models
Computational and Biological Learning Seminar Series
A role for circadian rhythms in maintaining neuronal properties
Computational and Biological Learning Seminar Series
From Sensation to Conception: Theoretical Perspectives on Multisensory Perception and Cross-Modal Transfer
Computational Neuroscience
Synaptic origins of working memory capacity
Computational and Biological Learning Seminar Series
Perspectives on Designing Optimal User Interfaces
Machine Learning @ CUED
Inference and Learning in the Anglican Probabilistic Programming System
Computational and Biological Learning Seminar Series
Approximate Message Passing Algorithms
Computational Neuroscience
Brain State Control by Closed-Loop Environmental Feedback
Machine Learning @ CUED
Unsupervised Risk Estimation with only Structural Assumptions
Computational Neuroscience
The stabilized supralinear network: A simple "balanced network" mechanism explaining nonlinear cortical integration
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
Machine Learning @ CUED
A more Automated Statistician
Computational Neuroscience
Probabilistic synapses
Machine Learning @ CUED
General Reinforcement Learning
Computational Neuroscience
The contribution of millisecond spike timing of cortical neurons to sensory coding and perceptual decisions
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Inference of a partially observed kinetic Ising model
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Meta-Bayesian Analysis
Computational Neuroscience
Approximate nonlinear filtering with a neural network
Machine Learning @ CUED
Efficient Inference and Learning with Intractable Posteriors? Yes, Please.
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Daleβs principle and the neural processing of latent factors
Computational Neuroscience
Decoding of complex stimuli from large retinal populations
Computational Neuroscience
Complementary approaches to Synaptic Plasticity: Objective Functions and Biophysics
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
Computational Neuroscience
A normative account of episodic memory in online learning over open model spaces
Machine Learning @ CUED
Scalable Gaussian Processes for Scientific Discovery
Machine Learning @ CUED
MCMC for non-linear state space models using ensembles of latent sequences
β οΈ (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
Computational Neuroscience
Contextual modulation of gamma rhythms in inhibition stabilized cortical networks
Machine Learning @ CUED
Modeling Confounding by Half-Sibling Regression
β οΈ SHORT TALK (20 minutes)
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
Computational Neuroscience
A three-threshold learning rule approaches the maximal capacity of recurrent neural networks
Computational Neuroscience
The statistical structure of noise in large neural populations
Machine Learning @ CUED
Random Function Classes for Machine Learning
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Unsupervised Learning with Latent Variable Models
Machine Learning @ CUED
Unsupervised Learning with Latent Variable Models
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Structural Markov laws / Geometry and HMC
Machine Learning @ CUED
Mean Field Approaches to Two Sequential Decision Making Problems.
β οΈ This talk will be given via Skype
Machine Learning @ CUED
Do Deep Nets Really Need to be Deep?
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Rogue states: altered dimensionality of neural circuit activity in Fragile-X mice
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Probabilistic numerics: treating numerical computation as learning, or; it's Bayes all the way down
Machine Learning @ CUED
Machine Learning for Quantitative Finance: A collaboration between the Cambridge Machine Learning Group and Cambridge Capital Management
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Title to be confirmed
Machine Learning @ CUED
Inference for infinite mixture models and Gaussian Process mixtures of experts using simple approximate MAP Inference
Machine Learning @ CUED
Evolutionary dynamics in a continuous public goods game
Machine Learning @ CUED
An introduction to the Mondrian Process
Computational Neuroscience
Dopamine - beyond reward?
Machine Learning @ CUED
Population Inference for Functional Brain Connectivity
Machine Learning @ CUED
Probabilistic approaches to understanding bird conversations
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
A* Sampling
Machine Learning @ CUED
Orthologous networks in biological systems
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Latent Branching Trees
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Experiments with Non-parametric Topic Models
Computational Neuroscience
Computational Neuroscience Course (4G3)
β οΈ 4G3 course -- repeats every Wed at 12noon, and Fri at 11am during Lent
Machine Learning @ CUED
The Blended Paradigm: A Bayesian Approach to Handling Outliers and Misspecified Models
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Machine Translation with LSTMs
β οΈ Room changed to LR3B in Inglis building and time changed to 10:30
Machine Learning @ CUED
Oracle Variational Inference
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Bayesian modeling for high-level real nursing activity recognition using accelerometers
β οΈ short talk
Computational Neuroscience
Chaos and entropy production in spiking networks
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
A Tutorial on Probabilistic Programming
Computational Neuroscience
Computational Neuroscience Journal Club
CUED Control Group Seminars
Optimal control and optimal sampling: A statistical physics perspective.
Computational Neuroscience
Sensory processing in neocortical networks: randomness, specificity and learning
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
New Methods in Bayesian Optimization for Machine Learning
Machine Learning @ CUED
A marginal sampler for Ο-Stable Poisson-Kingman mixture models
Machine Learning @ CUED
Local Deep Kernel Learning for Efficient Non-linear SVM Prediction
Computational Neuroscience
A Study of Certain Models of Synaptic Plasticity in the Cerebellum and Neocortex
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
Computational Neuroscience
Nervous system variability and robustness from cellular feedback control
Machine Learning @ CUED
Scalable Deep Gaussian Processes
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Active Learning of Linear Embeddings for Gaussian Processes
Computational Neuroscience
Computational Neuroscience Journal Club
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?
β οΈ NOTE THE SPECIAL VENUE (Microsoft Research)
Computational Neuroscience
Adaptation, coding and Bayesian computations in single neurons and neural populations
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Practical Machine Learning at Facebook. Examples and Lessons Learnt.
β οΈ Room changed to LR4
Machine Learning @ CUED
Bayesian inference for integer-valued LΓ©vy processes with Non-Gaussian Ornstein-Uhlenbeck volatility modelling
β οΈ short talk (30 mins) - NOTE TIME CHANGE
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
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Probabilistic computing applications: BayesDB and stochastic digital circuits
Machine Learning @ CUED
Probabilistic computing for Bayesian inference
Machine Learning @ CUED
Machine Learning and Order Book Dynamics
Machine Learning @ CUED
Policy Evaluation with Temporal Differences
Computational Neuroscience
Computational Neuroscience Journal Club
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
Machine Learning @ CUED
Parameter estimation in deep learning architectures: Two new insights.
β οΈ Note: time is 12 noon (*not* 11am)
Machine Learning @ CUED
Bayesian canonical correlation analysis
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Cambridge - Tuebingen PhD Applicant Talks (via Skype)
β οΈ Interview talks via Skype
Machine Learning @ CUED
Generative probabilistic programming: applications and new ideas
Machine Learning @ CUED
Bayesian nonparametrics: Dependency and Constraint Modeling
β οΈ Note: TALK via Skype!
Machine Learning @ CUED
Bayesian Nonparametric Model for Power Disaggregation
Machine Learning @ CUED
Probabilistic machine learning for knowledge extraction from videos and text
β οΈ Note venue: LR6
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Frequentist coverage of adaptive nonparametric Bayesian credible sets
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Course (4G3)
β οΈ 4G3 course -- repeats every Wed at 12am, and Fri at 11am during Lent
Machine Learning @ CUED
Anglican; Particle MCMC inference for Probabilistic Programs
Machine Learning @ CUED
Sparse discriminative latent characteristics for predicting cancer drug sensitivity
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Learning sensory and spatial representations from interacting excitatory and inhibitory synaptic plasticity
Computational Neuroscience
Neuronal processing of continuous sensory streams
Machine Learning @ CUED
Contrastive Learning Using Spectral Methods
Computational Neuroscience
Computational Neuroscience Journal Club
Computational and Biological Learning Seminar Series
Assembly and function of motor circuits for automatic and goal oriented movements
Computational and Biological Learning Seminar Series
A talk of two distinct parts: 1) a parametric empirical Bayesian approach to integration of fMRI, EEG and MEG data, 2) prediction error in episodic memory encoding
Computational Neuroscience
What the Rat's Whiskers Tell the Rat's Brain
Machine Learning @ CUED
Nonparametric Bayesian statistics with exchangeable random structures
Machine Learning @ CUED
Dissecting genotype to phenotype relationships
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
CANCELLED: Local Deep Kernel Learning for Efficient Non-linear SVM Prediction
β οΈ CANCELLED
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Clustering Based on Predictive Variances in Gaussian Process Regression Models
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
Machine Learning @ CUED
Annealing Between Distributions by Averaging Moments
NLIP Seminar Series
Recursive Deep Learning for Modeling Semantic Compositionality
Machine Learning @ CUED
Applied statistical genetics and next-generation association studies
Machine Learning @ CUED
Applied statistical genetics and next-generation association studies
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
The combinatorial structure of conditionally i.i.d. negative binomial processes directed by a beta process
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Optimal compensation for neuron death
jg691's list
Google's Approach to Building Relationships with Universities: Presentation and Talk by Dr David J Harper
Computational Neuroscience
Dendritic computation in pyramidal neurons.
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Matrix Concentration Inequalities via the Method of Exchangeable Pairs
Machine Learning @ CUED
Deep Gaussian Processes
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Approaches to statistical modeling of network data
Computational Neuroscience
Is the brain in a critical state?
Computational Neuroscience
Demixing scents: Sampling-based inference in olfaction.
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Bayesian nonparametric methods for non-exchangeable data
Machine Learning @ CUED
Non-parametric Bayesian Chromatin State Segmentation
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Fast Variational Inference in the Conjugate Exponential Family
Computational Neuroscience
University Lectureship in Computational Neuroscience candidate talks
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
An application of HDP And IBP for stream-based action recognition and high dimensional data
Machine Learning @ CUED
Using Context and Insight for the Analysis of LittleData?
Machine Learning @ CUED
Feature allocations, probability functions, and paintboxes
Machine Learning @ CUED
Modelling Reciprocating Relationships with Hawkes Processes
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Course (4G3)
β οΈ 4G3 course -- repeats Wednesdays at 12noon, Thursday at 2pm during Lent 2013
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
The combinatorial structure underlying a beta processes is that of a continuum of Blackwell-MacQueen urn schemes
Machine Learning @ CUED
Learning of Milky Way Model Parameters Using Matrix-variate Data in a New Gaussian Process-based Method
Computational Neuroscience
Computational Neuroscience Journal Club
bbu20's list
Coding with Dendrites
Computational Neuroscience
Computational Neuroscience Journal Club
Foster Talks
Space, sleep, brain rhythms and memory
Machine Learning @ CUED
Identification of causal effects
Machine Learning @ CUED
Probabilistic methods for biomolecular structure simulations
Computer Laboratory Systems Research Group Seminar
Distributed, Real-Time Bayesian Learning in Online Services
Computational Neuroscience
Computational Neuroscience Journal Club
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
β οΈ 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
Machine Learning @ CUED
Efficient Sampling with Kernel Herding
Computational Neuroscience
Perceiving is Believing: Bayesian inference in unexpected places.
Machine Learning @ CUED
Frank-Wolfe optimization insights in machine learning
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
Machine Learning @ CUED
Human Behavior Classification with Infinite Hidden Conditional Random Fields
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
Computational Neuroscience
Computational Neuroscience Journal Club
Computational and Biological Learning Seminar Series
Optimal integration of top-down and bottom-up uncertainty in humans, monkeys, and neural networks
Machine Learning @ CUED
Discovery of Complex Behaviors through Contact-Invariant Optimization
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Learning with nonparametric dependence and divergence estimation
Machine Learning @ CUED
Past work and future interests: respectively, the scattering of Anyons and Monte Carlo methods
Computational Neuroscience
Visuomotor behavior in naturalistic tasks: from receptive fields to value functions
Machine Learning @ CUED
Non-parametric Bayesian Method and Maximum-A-Posteriori Inference in Statistical Machine Translation
Computational and Biological Learning Seminar Series
Optimal encoding and decoding in sensory populations
Craik Club
"Probing sensory representations with metameric stimuli"
β οΈ The host for this talk is MΓ‘tΓ© Lengyel, Engineering Department. Note that the title and topic of the talk have been revised.
Adrian Seminars in Neuroscience
Near-optimal integration of evidence for decision-making in the rat.
Computational Neuroscience
Rational learning may be minimalist
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Infinite Structured Explicit Duration Hidden Markov Models
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Probabilistic computing: computation as universal stochastic inference, not deterministic calculation
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Scaling Machine Learning for the Internet
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Bayesian Quadrature for Prediction and Optimisation
Computational Neuroscience
Modeling a non-linear EPSPs integration site in dendrites and its impact on computational capacities
Machine Learning @ CUED
Efficient MCMC for Continuous Time Discrete State Systems
Machine Learning @ CUED
A Maximum Entropy Perspective on Spectral Dimensionality Reduction
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Variational Inference for Non-Conjugate Models
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Not so naive Bayesian classification
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Bayesian Nonparametrics: Latent Feature and Prediction Models, and Efficient Inference
Machine Learning @ CUED
Machine Learning Markets
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Factored Shapes and Appearances for Parts-based Object Understanding AND Transformation Equivariant Boltzmann Machines
Computational Neuroscience
Reconciling intuitive and Newtonian physics
Machine Learning @ CUED
Optimal Reinforcement Learning for Gaussian Systems
Machine Learning @ CUED
Exclusive PΓ³lya Urns and their applications
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Approximate Bayesian Inference for Large Scale Inverse Problems: A Computational Viewpoint
Machine Learning @ CUED
Some Practical Reflections on Graphical Models
Machine Learning @ CUED
Beyond Keyword Search: Discovering Relevant Scientific Literature
Machine Learning @ CUED
Graphical Models for Bandit Problems
Machine Learning @ CUED
Bayesian regression and classification with multivariate sparsifying priors
Computational Neuroscience
Organization of neuronal population activity in auditory cortex.
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
An FX trading system using adaptive reinforcement learning
β οΈ (rescheduled from May 24th)
Machine Learning @ CUED
Censored Exploration in Dark Pools
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
An FX trading system using adaptive reinforcement learning
β οΈ RESCHEDULED FOR JUNE 7th
Computational Neuroscience
Computational Neuroscience Journal Club
Craik Club
Navigational guidance systems in the human brain
β οΈ The host for this talk is Dr. MΓ‘tΓ© Lengyel, Engineering Dept.
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
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Nonlinear Dynamics of Learning
Machine Learning @ CUED
Exponential Conditional Volatility Models
Machine Learning @ CUED
Challenges in implementing the Bayesian paradigm
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 @ CUED
Title to be confirmed
Computational Neuroscience
Computational Neuroscience Journal Club
Craik Club
Conserved principles of movement generation
β οΈ The host for this talk is Dr. MΓ‘tΓ© Lengyel, Engineering Dept., m.lengyel@eng.cam.ac.uk
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Differential Geometric MCMC Methods
Machine Learning @ CUED
Mining viral datasets
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Universal Bayesian Agents: Theory and Applications
Machine Learning @ CUED
Machine learning in cancer research (a.k.a CRI meets CUED)
β οΈ (note new date)
Machine Learning @ CUED
Novi Quadrianto
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Learning item trees for collaborative filtering with implicit feedback
Machine Learning @ CUED
Non-Smooth-Norm Image Reconstruction from Noisy Data
Machine Learning @ CUED
Crowdsourcing data modelling
Computational Neuroscience
Computational neuroscience journal club
Machine Learning @ CUED
Short talks: Mixed Cumulative Distribution Networks; Nonparametric Bayesian community discovery in social networks; Expectation Propagation for Dirichlet Process Mixture Models
Computational Neuroscience
Parallel dendritic processing and hippocampal spatial representations
Zangwill Club
How the brain makes decisions
β οΈ Tea and Cakes available in 2nd Floor Seminar Room from 4pm
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Searching for Knowledge Instead of Web Pages
Computational Neuroscience
Optimality among optimals: decision making from neurobiological βnoisyβ signals within the cortico-basal-ganglia system
Machine Learning @ CUED
Bayesian Inference with Kernels
Computational and Biological Learning Seminar Series
Continuous control of brain computer interfaces based on a covert spatial attention paradigm
Computational Neuroscience
Translational biomedical informatics research in a clinical neurosurgery environment
Machine Learning @ CUED
On the Equivalence of Graph Cuts and Max-product Belief Propagation
Machine Learning @ CUED
Culture wars, voting and polarization: divisions and unities in modern American politics
β οΈ general audience talk (non-technical) -- NOTE change of room to LR4!
Machine Learning @ CUED
Creating structured and ο¬exible models: some open problems
Machine Learning @ CUED
Efficient Bayesian analysis of multiple changepoint models
Machine Learning @ CUED
Learning Common Grammar from Multilingual Corpus / Online Multiscale Dynamic Topic Models
Machine Learning @ CUED
Scalable Parallel Computing with CUDA
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
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 @ CUED
Structured Prediction Cascades
Machine Learning @ CUED
Parametric Bandits, Query Learning, and the Haystack Dimension
Computational Neuroscience
Learning predictive models for visual motion extrapolation
Computational Neuroscience
From tuning curves to behaviour
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Mapping affective decisions in depression using reinforcement learning tools
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Slice sampling with latent Gaussian models
Machine Learning @ CUED
Dynamic Network Tomography: Model, Algorithm, Theory, and Application
Machine Learning @ CUED
Making Sense of Data - A Research Agenda
Machine Learning @ CUED
Subspace Codes for Adversarial Error-Correction in Network Coding
β οΈ short talk
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Bayesian Inference in Networks of Queues
Machine Learning @ CUED
Stochastic Outlier Selection
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Mind Reading by Machine Learning: Optimal Experimental Design
β οΈ Short talk
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Machine Learning Course (4F13)
β οΈ 4F13 course - repeats Wed, Thurs at 10am during Lent
Machine Learning @ CUED
Machine Learning Course (4F13)
β οΈ 4F13 course - repeats Wed, Thurs at 10am during Lent
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Indian Buffet Processes with Power-law Behaviour
Machine Learning @ CUED
Gaussian Processes for Active Data Selection, Faults, Changepoints and Sensor Selection
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
KL control theory and decision making under uncertainty
Computational Neuroscience
Computational Neuroscience Journal Club
Adrian Seminars in Neuroscience
βModeling synaptic plasticity across multiple time scalesβ.
Machine Learning @ CUED
Information theoretic model selection in clustering
Computational Neuroscience
On the Games Neurons Play (in Visual Cortex)
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Motor Skills Learning for Robotics
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Reduced cortical neuron models: Experiment and theory
Machine Learning @ CUED
Coconut: Optimizing computations for machine learning
Computational Neuroscience
Computational Neuroscience Journal Club
Inference Group
Capacity of Spiking Neural Networks
Machine Learning @ CUED
Convex Variational Bayesian Inference for Large Scale Generalized Linear Models
Machine Learning @ CUED
Computable Probability Theory
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Is the homunculus `aware' of sensory adaptation?
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Using gradient descent for optimization and learning
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational and Biological Learning Seminar Series
Algorithms for Understanding Motor Cortical Processing and Neural Prosthetic Systems
Computational Neuroscience
Coding with envelopes, receptive fields and plasticity
Machine Learning @ CUED
Learning from Measurements in Exponential Families
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Shrinkage regression for multivariate inference with missing data, with an application to portfolio balancing
Machine Learning @ CUED
Quasi-linear Sensor Management
Computational Neuroscience
Computational Neuroscience Journal Club
Computational and Biological Learning Seminar Series
Mind reading by machine learning: an ideal observer based analysis of cognitive scientific experiments
Machine Learning @ CUED
Generalization in Learning
Machine Learning @ CUED
Stochastic control as an inference problem
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Extending the Affinity Propagation Model
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
The Block Diagonal Infinite Hidden Markov Model
Machine Learning @ CUED
Probabilistic Graph Models for Debugging Software
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
HMMs for Protein Sequencing from Mass Spectrometry Data
Machine Learning @ CUED
Mondrian Processes
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Hardness Ratios
Machine Learning @ CUED
Consensus finding, exponential models and infinite rankings
Computational Neuroscience
Computational Neuroscience Journal Club
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Foundations of Nonparametric Bayesian Methods (Part III)
Machine Learning @ CUED
Efficient Sequential Monte Carlo Inference for Kingman's Coalescent
β οΈ Note unusual time
Machine Learning @ CUED
Context in human robot interaction
Machine Learning @ CUED
Foundations of Nonparametric Bayesian Methods (Part II)
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Foundations of Nonparametric Bayesian Methods (Part I)
Machine Learning @ CUED
Shared Segmentation of Natural Scenes using Dependent Pitman-Yor Processes
Probabilistic Systems, Information, and Inference Group Seminars
From calcium imaging to spikes, using sequential Monte Carlo methods
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Spoken Dialogue Management
Machine Learning @ CUED
A Bayesian approach to language learning
Machine Learning @ CUED
Learning Bigrams from Unigrams
Machine Learning @ CUED
Nonparametric Bayesian Natural Language Model Domain Adaptation: A Hierarchical, Hierarchical Pitman-Yor Process Language Model
Computational Neuroscience
Computational Neuroscience Journal Club
Machine Learning @ CUED
Bayesian approaches to autonomous Bayesian real-time learning
Machine Learning @ CUED
Non-negative matrix factorization with Gaussian process priors
Machine Learning @ CUED
Matrix Factorization and Relational Learning
Computational Neuroscience
Assessing the effects of statistical dependencies on neural population coding in the visual pathway
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 @ CUED
Bayesian analysis of complex biological systems
Machine Learning @ CUED
Variational inference for partially observed diffusion processes
Computational and Biological Learning Seminar Series
Seeing Patterns in Randomness: Irrational Superstition or Adaptive Behavior?
Machine Learning @ CUED
Assessing high-dimensional latent variable models
Machine Learning @ CUED
Identification of dynamical subpopulations, optimal experiment design and more
Machine Learning @ CUED
H-Infinity Clustering
Machine Learning @ CUED
Sustainable Energy - without the hot air
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 @ CUED
An Introduction to Statistical Learning Theory
β οΈ Machine Learning Tutorial Lecture
Machine Learning @ CUED
Beam Sampling for Infinite Hidden Markov Models
Machine Learning @ CUED
Learning quantum physics
Machine Learning @ CUED
Convergence analysis of the EM algorithm and joint minimization of free energy
Machine Learning @ CUED
Discriminative Methods with Structure
Machine Learning @ CUED
A Bayesian approach to network modularity: inferring the structure and scale of modular networks
Machine Learning @ CUED
Model selection and model order adaptation for clustering
Machine Learning @ CUED
Expectation Propagation, Experimental Design for the Sparse Linear Model
Machine Learning @ CUED
Biomedical Image Search
Machine Learning @ CUED
Stable distribution and data sketching
Machine Learning @ CUED
Reinforcement Learning
β οΈ Machine Learning Tutorial Lecture (Note unusual day)
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 @ CUED
Gene Regulatory Network Inference: A Kernel-Based Learning Approach
Machine Learning @ CUED
Clinical data based optimal STI strategies for HIV: a reinforcement learning approach
Machine Learning @ CUED
Machine Learning Applications / Challenges in Natural Language Parsing
β οΈ Machine Learning Tutorial Lecture
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 @ CUED
Hidden Common Cause Relations in Relational Learning
Machine Learning @ CUED
Optimal Spreading Sequences for Chaos-Based Communication Systems; Using CSK as a Case Study
Machine Learning @ CUED
Graph Kernels for Data Mining
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
Computational and Biological Learning Seminar Series
A new mathematical framework for optimal choice of actions
Machine Learning @ CUED
Logistic Regression with a Laplacian prior on the Eigenvalues: Convex duality and application to EEG classification
β οΈ Note different room and time
Machine Learning @ CUED
Dirichlet Processes and Hierarchical Dirichlet Processes
β οΈ Advanced Machine Learning Tutorial Lecture
Machine Learning @ CUED
An Introduction to Non-parametric Bayesian Methods
β οΈ Room changed this week!
Machine Learning @ CUED
Robot Localisation and Mapping
β οΈ Advanced Machine Learning Tutorial Lecture
Machine Learning @ CUED
Gaussian Processes for Machine Learning
β οΈ Advanced Machine Learning Tutorial Lecture
Machine Learning @ CUED
Mixture Models and the EM Algorithm
β οΈ Advanced Machine Learning Tutorial Lecture
Machine Learning @ CUED
Probabilistic Dimensional Reduction with the Gaussian Process Latent Variable Model
Please see above for contact details for this list.