What's in a Prior? Learned Proximal Networks for Inverse Problems

22 October 2023

Papers citing "What's in a Prior? Learned Proximal Networks for Inverse Problems"

15 / 15 papers shown

Title
Good Things Come in Pairs: Paired Autoencoders for Inverse Problems Matthias Chung B. Peters Michael Solomon 29 0 0 10 May 2025
Your contrastive learning problem is secretly a distribution alignment problem Zihao Chen Chi-Heng Lin Ran Liu Jingyun Xiao Eva L. Dyer 67 1 0 27 Feb 2025
The Star Geometry of Critic-Based Regularizer Learning Oscar Leong Eliza O'Reilly Yong Sheng Soh AAML 42 0 0 29 Aug 2024
Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching Yasi Zhang Peiyu Yu Yaxuan Zhu Yingshan Chang Feng Gao Yingnian Wu Oscar Leong 75 7 0 29 May 2024
Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors Zihui Wu Yu Sun Yifan Chen Bingliang Zhang Yisong Yue Katherine L. Bouman DiffM 27 20 0 29 May 2024
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction Xingyu Xu Yuejie Chi DiffM 42 20 0 25 Mar 2024
Score-Based Diffusion Models as Principled Priors for Inverse Imaging Berthy T. Feng Jamie Smith Michael Rubinstein Huiwen Chang Katherine L. Bouman William T. Freeman DiffM 84 87 0 23 Apr 2023
Provably Convergent Plug-and-Play Quasi-Newton Methods Hongwei Tan Subhadip Mukherjee Junqi Tang Carola-Bibiane Schönlieb 26 13 0 09 Mar 2023
DeepSTI: Towards Tensor Reconstruction using Fewer Orientations in Susceptibility Tensor Imaging Zhenghan Fang Kuo-Wei Lai P. Zijl Xu Li Jeremias Sulam 21 5 0 09 Sep 2022
Online Deep Equilibrium Learning for Regularization by Denoising Jiaming Liu Xiaojian Xu Weijie Gan S. Shoushtari Ulugbek S. Kamilov 29 26 0 25 May 2022
Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularization Samuel Hurault Arthur Leclaire Nicolas Papadakis 47 72 0 31 Jan 2022
Denoising Diffusion Restoration Models Bahjat Kawar Michael Elad Stefano Ermon Jiaming Song DiffM 212 778 0 27 Jan 2022
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 112 95 0 10 Dec 2020
Deep Unfolding Network for Image Super-Resolution K. Zhang Luc Van Gool Radu Timofte SupR 108 538 0 23 Mar 2020
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 173 597 0 22 Sep 2016