
J.W.Stevens
Name:  J.W.Stevens 
Affiliation:  University of Cambridge 
Email:  (only provided to users who are logged into talks.cam) 
Last login:  Wed Jan 19 13:17:20 +0000 2022 
Public lists managed by J.W.Stevens
Talks given by J.W.Stevens
Obviously this only lists talks that are listed through talks.cam. Furthermore, this facility only works if the speaker's email was specified in a talk. Most talks have not done this.
Talks organised by J.W.Stevens
This list is based on what was entered into the 'organiser' field in a talk. It may not mean that J.W.Stevens actually organised the talk, they may have been responsible only for entering the talk into the talks.cam system.
 Deep Learning for Inverse Problems in Medical Imaging
 Equivariant Imaging: Unsupervised Learning in Inverse Problems
 Deep Learning Enables Prostate MRI Segmentation and Cancer Classification
 Genomewide Association Analysis of Blood Smear Imaging Phenotypes
 Uncertainty Quantification of Inclusion Boundaries in the Context of Xray Tomography
 Testing breast cancer mammography screening artificial intelligence algorithms using the Cambridge Cohort database; study design, methods and statistical analysis
 Generative modelbased super resolution and quality control for cardiac segmentation
 Practical Challenges in Portfolio Construction
 Iteratively Reweighted FGMRES and FLSQR for sparse reconstruction
 A nonparametric problem for stochastic PDEs
 Methods for interactive medical imaging
 Imaging & Mathematics Network Meeting  Lent term
 The Cycle of Statistical Research
 Lecture 4: Computational methods based on MetropolisHastings (note: different time and room)
 Lecture 3: Computational methods based on Monte Carlo and Importance Sampling
 Lecture 2: Inverse problems in PDEs, Infinite dimensional inverse problems
 Lecture 1: Inverse problems, Bayes' theorem, Connection to regularisation and optimisation
 Nonparametric Bayesian Methods: Models, Algorithms, and Applications (Lecture 3)
 Mathematics can make my medical imaging faster and prettier – but should it?
 Nonparametric Bayesian Methods: Models, Algorithms, and Applications (Lecture 2)
 Nonparametric Bayesian Methods: Models, Algorithms, and Applications (Lecture 1)
 Variational Bayes and Beyond: Foundations of Scalable Bayesian Inference
 Imaging & Mathematics Network Meeting  Michaelmas
 Collaborative Analytics and Education in Data Science
 Artificial Intelligence in Radiology: Where Does It Stand and Where Is It Going?
 CCIMI Short Course Lecture 4
 CCIMI Short Course Lecture 3
 CCIMI Short Course Lecture 2
 CCIMI Short Course Lecture 1
 Valuedbased Healthcare and Healthcare Supply Chains
 On the mode of multivariate mixtures — recent developments and open problems
 Deformable image registration of abdominal CT images using deep learning: challenges and opportunities
 Learned image reconstruction for large scale tomographic imaging
 Lecture 5: Other constructions on graphs (discrete optimal transport)
 Lecture 4: Consistency results. Spectral methods, Calculus of Variations methods, PDE methods. Part 3
 Lecture 3: Consistency results. Spectral methods, Calculus of Variations methods, PDE methods. Part 2
 Lecture 2: Consistency results. Spectral methods, Calculus of Variations methods, PDE methods. Part 1
 Lecture 1: Introduction. How can geometry help us learn from data? Optimization and Bayesian approaches.
 CCIMI Video Contest
 Stochastic variants of classical optimization methods, with complexity guarantees
 Nigrolstriatal Degeneration in EarlyStage Pakinson’s Disease Using Quantitative Susceptibility Mapping and 18FDTBZ PET: a Pilot Study
 Noncontrast Enhanced MRI in Central Nervous System
 A variational approach to nonlinear and interacting diffusions
 Improving the Flexibility and Robustness of DerivativeFree Optimization Solvers
 Texture analysis and Machine Learning for the Prediction of Cardiovascular Events
 Pure Mathematics in Crisis
 GenOja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation
 Adaptive and robust nonparametric Bayesian contraction rates for discretely observed compound Poisson processes
 Estimation of LowRank Matrices via Approximate Message Passing
