755 citations · 1.6k across the 34 of their papers we have counts for
4 papers · 1 filter
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…
Learned Primal-dual Reconstruction
Jonas Adler, Ozan Öktem
We propose the Learned Primal-Dual algorithm for tomographic reconstruction. The algorithm accounts for a (possibly non-linear) forward operator in a deep neural network by unrolli…
Indirect Image Registration with Large Diffeomorphic Deformations
Chong Chen, Ozan Öktem
The paper adapts the large deformation diffeomorphic metric mapping framework for image registration to the indirect setting where a template is registered against a target that is…
Solving ill-posed inverse problems using iterative deep neural networks
Jonas Adler, Ozan Öktem
We propose a partially learned approach for the solution of ill posed inverse problems with not necessarily linear forward operators. The method builds on ideas from classical regu…