Learning to solve inverse problems using Wasserstein loss

Jonas Adler, Axel Ringh, Ozan Öktem +1

We propose using the Wasserstein loss for training in inverse problems. In particular, we consider a learned primal-dual reconstruction scheme for ill-posed inverse problems using…