Total Deep Variation: A Stable Regularizer for Inverse Problems

Total Deep Variation: A Stable Regularizer for Inverse Problems

15 June 2020

Alexander Effland

Papers citing "Total Deep Variation: A Stable Regularizer for Inverse Problems"

13 / 13 papers shown

Title
A Generalization Result for Convergence in Learning-to-Optimize Michael Sucker Peter Ochs 26 0 0 10 Oct 2024
Optimal Regularization for a Data Source Oscar Leong Eliza O'Reilly Yong Sheng Soh V. Chandrasekaran 14 4 0 27 Dec 2022
Learning-Assisted Algorithm Unrolling for Online Optimization with Budget Constraints Jianyi Yang Shaolei Ren 10 2 0 03 Dec 2022
PAC-Bayesian Learning of Optimization Algorithms Michael Sucker Peter Ochs 11 4 0 20 Oct 2022
WARPd: A linearly convergent first-order method for inverse problems with approximate sharpness conditions Matthew J. Colbrook 21 2 0 24 Oct 2021
Learning to Optimize: A Primer and A Benchmark Tianlong Chen Xiaohan Chen Wuyang Chen Howard Heaton Jialin Liu Zhangyang Wang W. Yin 30 225 0 23 Mar 2021
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction Dominik Narnhofer Alexander Effland Erich Kobler Kerstin Hammernik Florian Knoll T. Pock UQCV BDL 15 49 0 12 Feb 2021
Can stable and accurate neural networks be computed? -- On the barriers of deep learning and Smale's 18th problem Matthew J. Colbrook Vegard Antun A. Hansen 65 129 0 20 Jan 2021
Shared Prior Learning of Energy-Based Models for Image Reconstruction Thomas Pinetz Erich Kobler T. Pock Alexander Effland DiffM 19 4 0 12 Nov 2020
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 19 101 0 09 Nov 2020
Iterative Methods for Computing Eigenvectors of Nonlinear Operators Guy Gilboa 10 4 0 06 Oct 2020
A Color Elastica Model for Vector-Valued Image Regularization Hao Liu X. Tai Ron Kimmel R. Glowinski 6 16 0 19 Aug 2020
Deep Unfolding Network for Image Super-Resolution K. Zhang Luc Van Gool Radu Timofte SupR 108 538 0 23 Mar 2020