Jonas Adler
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Recent & Upcoming Talks
2019
Invited Talk: Deep learning for inverse problems. Where are we, and how far can we go?
Feb 18, 2019
GAMM
PDF
Invited Talk: Deep Posterior Sampling
Feb 4, 2019
BASP Frontiers
PDF
Contributed Talk: Deep Bayesian Inversion
Jan 22, 2019
Deep Learning and Inverse Problems
PDF
2018
Invited Talk: Recent advances in using machine learning for image reconstruction
Dec 12, 2018
Seminar at New York University
PDF
Oral: Task adapted reconstruction for inverse problems
Dec 8, 2018
Medical imaging meets NeurIPS
PDF
Invited talk: Deep Learning for Image Reconstruction
Nov 20, 2018
University of Bath
PDF
Invited talk: Deep Learning for Image Reconstruction
Oct 19, 2018
Chinese Academy of Sciences
Invited talk: Learning to solve inverse problems with ODL
Jun 8, 2018
SIAM conference on imaging science
Invited talk: Learned Iterative Reconstruction for CT
Jun 8, 2018
SIAM conference on imaging science
Invited talk: What Can We Expect? Computable Upper Bounds to Machine Learning in Inverse Problems Using MCMC
Mar 23, 2018
High Performance Scientific Computing
Contributed talk: Learned iterative reconstruction
Mar 9, 2018
Swedish Symposium on Image Analysis
2017
Poster: Learning to solve inverse problems using Wasserstein Loss
Dec 9, 2017
Neural Information Processing Systems
Contributed talk: Learned forward operators: Variational regularization for black-box models
Oct 31, 2017
Generative models, parameter learning and sparsity
Invited talk: Learned iterative reconstruction schemes, theory and practice
Sep 18, 2017
Variational Methods Meet Machine Learning
Invited talk: Using deep learning to reconstruct multi-modal images - A primal dual scheme with examples in PET-MRI
May 31, 2017
Applied Inverse Problems
2015
ODL: A python library for inverse problems
Nov 15, 2015
IEEE Medical Imaging Conference
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