J.W.Stevens

Name:	J.W.Stevens
Affiliation:	University of Cambridge
E-mail:	(only provided to users who are logged into talks.cam)
Last login:	Mon Jun 27 23:19:34 +0000 2022

Public lists managed by J.W.Stevens

• CCIMI Short Course: Introduction to the Bayesian approach to inverse problems
• CCIMI Short Course: Mathematics of Data - From Theory to Computation
• CCIMI Short Course: Random matrices, Dyson-Schwinger equations and the topological expansion
• CCIMI Short Course: Tamara Broderick (MIT)
• CCIMI Short course - Graph-based Approaches to Learning: Mathematical Theory and Perspectives
• CCIMI Short course: First-order methods for large scale optimisation problems
• CCIMI short course: Quantum Computing - Theory and Practice
• CMIH Imaging Clinic
• CMIH short course: Image Reconstruction in Biomedical Imaging
• CRUK CI Light Microscopy Course
• Imaging & Mathematics: networking across disciplines
• Short Course: Higher order regularisation in imaging
• Type the title of a new list here

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 e-mail 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 in Endovascular Aneurysm Repair Surveillance
• Deep Learning for Inverse Problems in Medical Imaging
• Equivariant Imaging: Unsupervised Learning in Inverse Problems
• Deep Learning Enables Prostate MRI Segmentation and Cancer Classification
• Genome-wide Association Analysis of Blood Smear Imaging Phenotypes
• Uncertainty Quantification of Inclusion Boundaries in the Context of X-ray Tomography
• Testing breast cancer mammography screening artificial intelligence algorithms using the Cambridge Cohort database; study design, methods and statistical analysis
• Generative model-based 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 Metropolis-Hastings (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
• Valued-based 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 Early-Stage Pakinson’s Disease Using Quantitative Susceptibility Mapping and 18F-DTBZ PET: a Pilot Study
• Non-contrast Enhanced MRI in Central Nervous System
• A variational approach to nonlinear and interacting diffusions
• Improving the Flexibility and Robustness of Derivative-Free Optimization Solvers
• Texture analysis and Machine Learning for the Prediction of Cardiovascular Events
• Pure Mathematics in Crisis
• Gen-Oja: 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 Low-Rank Matrices via Approximate Message Passing