Gradient Step Denoiser for convergent Plug-and-Play

7 October 2021

Papers citing "Gradient Step Denoiser for convergent Plug-and-Play"

50 / 56 papers shown

Title
Learning Cocoercive Conservative Denoisers via Helmholtz Decomposition for Poisson Inverse Problems Deliang Wei Peng Chen Haobo Xu Jiale Yao Fang Li Tieyong Zeng 14 0 0 13 May 2025
PG-DPIR: An efficient plug-and-play method for high-count Poisson-Gaussian inverse problems Maud Biquard Marie Chabert Florence Genin Christophe Latry Thomas Oberlin 29 0 0 14 Apr 2025
Deep End-to-End Posterior ENergy (DEEPEN) for image recovery Jyothi Rikhab Chand M. Jacob DiffM 41 0 0 21 Mar 2025
Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems Teresa Klatzer Savvas Melidonis Marcelo Pereyra K. Zygalakis 47 0 0 20 Mar 2025
From Denoising Score Matching to Langevin Sampling: A Fine-Grained Error Analysis in the Gaussian Setting Samuel Hurault M. Terris Thomas Moreau Gabriel Peyré DiffM 41 1 0 14 Mar 2025
Reconstruct Anything Model: a lightweight foundation model for computational imaging M. Terris Samuel Hurault Maxime Song Julian Tachella MedIm DiffM 70 2 0 11 Mar 2025
RestoreGrad: Signal Restoration Using Conditional Denoising Diffusion Models with Jointly Learned Prior Ching Hua Lee Chouchang Yang Jaejin Cho Yashas Malur Saidutta R. S. Srinivasa Yilin Shen Hongxia Jin DiffM 85 0 0 19 Feb 2025
Gradient Networks Shreyas Chaudhari Srinivasa Pranav J. M. F. Moura 50 0 0 28 Jan 2025
Analysis and Synthesis Denoisers for Forward-Backward Plug-and-Play Algorithms M. Kowalski Benoit Malézieux Thomas Moreau Audrey Repetti 72 0 0 20 Nov 2024
Classification-Denoising Networks Louis Thiry Florentin Guth 34 0 0 04 Oct 2024
PnP-Flow: Plug-and-Play Image Restoration with Flow Matching Ségolène Martin Anne Gagneux Paul Hagemann Gabriele Steidl 42 9 0 03 Oct 2024
A Unified Plug-and-Play Algorithm with Projected Landweber Operator for Split Convex Feasibility Problems Shuchang Zhang Hongxia Wang 21 0 0 22 Aug 2024
HPPP: Halpern-type Preconditioned Proximal Point Algorithms and Applications to Image Restoration Shuchang Zhang Hui Zhang Hongxia Wang 53 0 0 18 Jul 2024
Stability of Data-Dependent Ridge-Regularization for Inverse Problems Sebastian Neumayer Fabian Altekrüger 34 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 67 1 0 08 Apr 2024
Learning pseudo-contractive denoisers for inverse problems Deliang Wei Peng Chen Fang Li 22 4 0 08 Feb 2024
Plug-and-Play image restoration with Stochastic deNOising REgularization Marien Renaud Jean Prost Arthur Leclaire Nicolas Papadakis DiffM 52 7 0 01 Feb 2024
Low-resolution Prior Equilibrium Network for CT Reconstruction Yijie Yang Qifeng Gao Yuping Duan 24 0 0 28 Jan 2024
Learned reconstruction methods for inverse problems: sample error estimates Luca Ratti 24 0 0 21 Dec 2023
Equivariant plug-and-play image reconstruction M. Terris Thomas Moreau Nelly Pustelnik Julian Tachella 31 16 0 04 Dec 2023
Meta-Prior: Meta learning for Adaptive Inverse Problem Solvers M. Terris Thomas Moreau 24 0 0 30 Nov 2023
Variational Bayes image restoration with compressive autoencoders Maud Biquard Marie Chabert Thomas Oberlin 19 1 0 29 Nov 2023
Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging M. Carioni Subhadip Mukherjee Hongwei Tan Junqi Tang MedIm 29 3 0 15 Nov 2023
Convergent plug-and-play with proximal denoiser and unconstrained regularization parameter Samuel Hurault A. Chambolle Arthur Leclaire Nicolas Papadakis 21 5 0 02 Nov 2023
What's in a Prior? Learned Proximal Networks for Inverse Problems Zhenghan Fang Sam Buchanan Jeremias Sulam 31 11 0 22 Oct 2023
Provably Convergent Data-Driven Convex-Nonconvex Regularization Zakhar Shumaylov Jeremy Budd Subhadip Mukherjee Carola-Bibiane Schönlieb 32 5 0 09 Oct 2023
Batch-less stochastic gradient descent for compressive learning of deep regularization for image denoising Hui Shi Yann Traonmilin Jean-François Aujol 6 0 0 02 Oct 2023
Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis S. Shoushtari Jiaming Liu Edward P. Chandler M. Salman Asif Ulugbek S. Kamilov 24 3 0 29 Sep 2023
Fast Diffusion EM: a diffusion model for blind inverse problems with application to deconvolution Charles Laroche Andrés Almansa Eva Coupeté DiffM 17 26 0 01 Sep 2023
Learning Weakly Convex Regularizers for Convergent Image-Reconstruction Algorithms Alexis Goujon Sebastian Neumayer M. Unser 41 23 0 21 Aug 2023
Convergent regularization in inverse problems and linear plug-and-play denoisers A. Hauptmann Subhadip Mukherjee Carola-Bibiane Schönlieb Ferdia Sherry 21 13 0 18 Jul 2023
Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems Samuel Hurault Ulugbek Kamilov Arthur Leclaire Nicolas Papadakis 16 10 0 06 Jun 2023
Block Coordinate Plug-and-Play Methods for Blind Inverse Problems Weijie Gan S. Shoushtari Yuyang Hu Jiaming Liu Hongyu An Ulugbek S. Kamilov 20 11 0 22 May 2023
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems Ziruo Cai Junqi Tang Subhadip Mukherjee Jinglai Li Carola Bibiane Schönlieb Xiaoqun Zhang AI4CE 28 3 0 17 Apr 2023
RED-PSM: Regularization by Denoising of Factorized Low Rank Models for Dynamic Imaging Berk Iskender M. Klasky Y. Bresler 25 3 0 07 Apr 2023
Inverse problem regularization with hierarchical variational autoencoders Jean Prost Antoine Houdard Andrés Almansa Nicolas Papadakis 16 4 0 20 Mar 2023
Fluctuation-based deconvolution in fluorescence microscopy using plug-and-play denoisers V. Stergiopoulou Subhadip Mukherjee L. Calatroni Laure Blanc-Féraud 6 3 0 20 Mar 2023
Provably Convergent Plug-and-Play Quasi-Newton Methods Hongwei Tan Subhadip Mukherjee Junqi Tang Carola-Bibiane Schönlieb 28 13 0 09 Mar 2023
Restoration based Generative Models Jaemoo Choi Yesom Park Myung-joo Kang DiffM AI4CE 31 5 0 20 Feb 2023
A relaxed proximal gradient descent algorithm for convergent plug-and-play with proximal denoiser Samuel Hurault A. Chambolle Arthur Leclaire Nicolas Papadakis 14 11 0 31 Jan 2023
A Neural-Network-Based Convex Regularizer for Inverse Problems Alexis Goujon Sebastian Neumayer Pakshal Bohra Stanislas Ducotterd M. Unser 13 26 0 22 Nov 2022
Robustness of Deep Equilibrium Architectures to Changes in the Measurement Model Jun-Hao Hu S. Shoushtari Zihao Zou Jiaming Liu Zhixin Sun Ulugbek S. Kamilov 51 4 0 01 Nov 2022
Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions Stanislas Ducotterd Alexis Goujon Pakshal Bohra Dimitris Perdios Sebastian Neumayer M. Unser 35 12 0 28 Oct 2022
Neural Conservation Laws: A Divergence-Free Perspective Jack Richter-Powell Y. Lipman Ricky T. Q. Chen 46 50 0 04 Oct 2022
Video Restoration with a Deep Plug-and-Play Prior Antoine Monod J. Delon Matias Tassano Andrés Almansa 25 1 0 06 Sep 2022
Deep Model-Based Architectures for Inverse Problems under Mismatched Priors S. Shoushtari Jiaming Liu Yuyang Hu Ulugbek S. Kamilov 26 6 0 26 Jul 2022
Learned reconstruction methods with convergence guarantees Subhadip Mukherjee A. Hauptmann Ozan Oktem Marcelo Pereyra Carola-Bibiane Schönlieb 22 49 0 11 Jun 2022
Automatic differentiation of nonsmooth iterative algorithms Jérôme Bolte Edouard Pauwels Samuel Vaiter 15 21 0 31 May 2022
Online Deep Equilibrium Learning for Regularization by Denoising Jiaming Liu Xiaojian Xu Weijie Gan S. Shoushtari Ulugbek S. Kamilov 31 26 0 25 May 2022
PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization Fabian Altekrüger Alexander Denker Paul Hagemann J. Hertrich Peter Maass Gabriele Steidl MedIm 16 24 0 24 May 2022