Invited Talk: Deep learning for inverse problems. Where are we, and how far can we go?18 February 2019GAMM — Vienna, Austria
Contributed Talk: Deep Bayesian Inversion22 January 2019Deep Learning and Inverse Problems — Stockholm, Sweden
Invited Talk: Recent advances in using machine learning for image reconstruction12 December 2018Seminar at New York University — New York, USA
Oral: Task adapted reconstruction for inverse problems8 December 2018Medical imaging meets NeurIPS — Montreal, Canada
Invited talk: Deep Learning for Image Reconstruction4 November 2018University of Bath — Bath, England
Invited talk: Deep Learning for Image Reconstruction19 October 2018Chinese Academy of Sciences — Beijing, China
Invited talk: Learning to solve inverse problems with ODL8 June 2018SIAM conference on imaging science — Bologna, Italy
Invited talk: Learned Iterative Reconstruction for CT8 June 2018SIAM conference on imaging science — Bologna, Italy
Invited talk: What Can We Expect? Computable Upper Bounds to Machine Learning in Inverse Problems Using MCMC23 March 2018High Performance Scientific Computing — Hanoi, Vietnam
Contributed talk: Learned iterative reconstruction9 March 2018Swedish Symposium on Image Analysis — Stockholm, Sweden
Poster: Learning to solve inverse problems using Wasserstein Loss9 December 2017Neural Information Processing Systems — Los Angeles, USA
Contributed talk: Learned forward operators: Variational regularization for black-box models31 October 2017Generative models, parameter learning and sparsity — Cambridge, UK
Invited talk: Learned iterative reconstruction schemes, theory and practice18 September 2017Variational Methods Meet Machine Learning — Cambridge, UK
Invited talk: Using deep learning to reconstruct multi-modal images - A primal dual scheme with examples in PET-MRI31 May 2017Applied Inverse Problems — Hangzhou, China
ODL: A python library for inverse problems15 November 2015IEEE Medical Imaging Conference — San Diego, USA