Learned reconstruction methods with convergence guarantees

Learned reconstruction methods with convergence guarantees

11 June 2022

Subhadip Mukherjee

Marcelo Pereyra

Carola-Bibiane Schönlieb

Papers citing "Learned reconstruction methods with convergence guarantees"

11 / 11 papers shown

Title
Tuning-Free Structured Sparse PCA via Deep Unfolding Networks Long Chen Xianchao Xiu 210 0 0 28 Feb 2025
Bayesian computation with generative diffusion models by Multilevel Monte Carlo Abdul-Lateef Haji-Ali Marcelo Pereyra Luke Shaw K. Zygalakis DiffM 47 0 0 23 Sep 2024
Stability of Data-Dependent Ridge-Regularization for Inverse Problems Sebastian Neumayer Fabian Altekrüger 42 1 0 18 Jun 2024
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation Hongwei Tan Ziruo Cai Marcelo Pereyra Subhadip Mukherjee Junqi Tang Carola-Bibiane Schönlieb SSL 73 1 0 08 Apr 2024
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction Moritz Piening Fabian Altekrüger J. Hertrich Paul Hagemann Andrea Walther Gabriele Steidl 29 6 0 27 Dec 2023
Inverse Problems with Learned Forward Operators Simon Arridge Andreas Hauptmann Yury Korolev 43 1 0 21 Nov 2023
Learning Weakly Convex Regularizers for Convergent Image-Reconstruction Algorithms Alexis Goujon Sebastian Neumayer M. Unser 41 23 0 21 Aug 2023
Model-corrected learned primal-dual models for fast limited-view photoacoustic tomography A. Hauptmann Jenni Poimala MedIm 33 5 0 04 Apr 2023
Fixed-Point and Objective Convergence of Plug-and-Play Algorithms Pravin Nair Ruturaj G. Gavaskar K. Chaudhury 48 37 0 21 Apr 2021
Regularization by Denoising: Clarifications and New Interpretations E. T. Reehorst Philip Schniter 56 214 0 06 Jun 2018
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 187 601 0 22 Sep 2016