Invited Talk: Deep learning for inverse problems. Where are we, and how far can we go?
GAMM — Vienna, Austria
Talks
2019
2018
Invited Talk: Recent advances in using machine learning for image reconstruction
Seminar at New York University — New York, USA
Oral: Task adapted reconstruction for inverse problems
Medical imaging meets NeurIPS — Montreal, Canada
Invited talk: Learning to solve inverse problems with ODL
SIAM conference on imaging science — Bologna, Italy
Invited talk: Learned Iterative Reconstruction for CT
SIAM conference on imaging science — Bologna, Italy
Invited talk: What Can We Expect? Computable Upper Bounds to Machine Learning in Inverse Problems Using MCMC
High Performance Scientific Computing — Hanoi, Vietnam
Contributed talk: Learned iterative reconstruction
Swedish Symposium on Image Analysis — Stockholm, Sweden
2017
Poster: Learning to solve inverse problems using Wasserstein Loss
Neural Information Processing Systems — Los Angeles, USA
Contributed talk: Learned forward operators: Variational regularization for black-box models
Generative models, parameter learning and sparsity — Cambridge, UK
Invited talk: Learned iterative reconstruction schemes, theory and practice
Variational Methods Meet Machine Learning — Cambridge, UK
Invited talk: Using deep learning to reconstruct multi-modal images - A primal dual scheme with examples in PET-MRI
Applied Inverse Problems — Hangzhou, China