Neural Proximal Gradient Descent for Compressive Imaging

1 June 2018

Morteza Mardani

Qingyun Sun

Shreyas S. Vasawanala

Papers citing "Neural Proximal Gradient Descent for Compressive Imaging"

50 / 72 papers shown

Title
Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Yasar Utku Alçalar Mehmet Akçakaya 29 1 0 30 May 2025
Comprehensive Examination of Unrolled Networks for Solving Linear Inverse Problems Eric Chen Xi Chen A. Maleki S. Jalali 155 0 0 08 Jan 2025
Injectivity capacity of ReLU gates Mihailo Stojnic 70 0 0 28 Oct 2024
A Unified Model for Compressed Sensing MRI Across Undersampling Patterns Armeet Singh Jatyani Jiayun Wang Zihui Wu Miguel Liu-Schiaffini Bahareh Tolooshams Anima Anandkumar Anima Anandkumar 77 2 0 05 Oct 2024
Controlled Learning of Pointwise Nonlinearities in Neural-Network-Like Architectures Michael Unser Alexis Goujon Stanislas Ducotterd 123 2 0 23 Aug 2024
Learning Regularization for Graph Inverse Problems Moshe Eliasof Md Shahriar Rahim Siddiqui Carola-Bibiane Schönlieb Eldad Haber GNN 195 0 0 19 Aug 2024
Graph Neural Reaction Diffusion Models Moshe Eliasof Eldad Haber Eran Treister DiffM AI4CE 98 3 0 16 Jun 2024
A Brief Overview of Optimization-Based Algorithms for MRI Reconstruction Using Deep Learning Wanyu Bian 119 7 0 03 Jun 2024
A General Continuous-Time Formulation of Stochastic ADMM and Its Variants Chris Junchi Li 71 0 0 22 Apr 2024
Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview Alexander Auras Kanchana Vaishnavi Gandikota Hannah Droege Michael Moeller AAML 72 0 0 19 Feb 2024
An Over Complete Deep Learning Method for Inverse Problems Moshe Eliasof Eldad Haber Eran Treister 54 3 0 07 Feb 2024
What's in a Prior? Learned Proximal Networks for Inverse Problems Zhenghan Fang Sam Buchanan Jeremias Sulam 86 12 0 22 Oct 2023
Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems Qingping Zhou Jiayu Qian Junqi Tang Jinglai Li AI4CE 66 5 0 30 Jul 2023
Feature Transportation Improves Graph Neural Networks Moshe Eliasof E. Haber Eran Treister GNN 109 12 0 29 Jul 2023
Towards Constituting Mathematical Structures for Learning to Optimize Jialin Liu Xiaohan Chen Zhangyang Wang W. Yin HanQin Cai 106 13 0 29 May 2023
DRIP: Deep Regularizers for Inverse Problems Moshe Eliasof E. Haber Eran Treister 90 8 0 30 Mar 2023
$Learning Trees of $\ell_0$-Minimization Problems$ Learning Trees of $\ell_0$ -Minimization Problems G. Welper 64 0 0 06 Feb 2023
Estimating a potential without the agony of the partition function E. Haber Moshe Eliasof L. Tenorio 61 2 0 19 Aug 2022
GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction Batu Mehmet Ozturkler Arda Sahiner Tolga Ergen Arjun D Desai Christopher M. Sandino S. Vasanawala John M. Pauly Morteza Mardani Mert Pilanci 50 4 0 18 Jul 2022
Uncertainty Quantification for Deep Unrolling-Based Computational Imaging Canberk Ekmekci Müjdat Çetin UQCV 107 12 0 02 Jul 2022
RU-Net: Regularized Unrolling Network for Scene Graph Generation Xin Lin Changxing Ding Jing Zhang Yibing Zhan Dacheng Tao 81 34 0 03 May 2022
PnP-ReG: Learned Regularizing Gradient for Plug-and-Play Gradient Descent Rita Fermanian Mikael Le Pendu C. Guillemot 73 7 0 29 Apr 2022
Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction Beliz Gunel Arda Sahiner Arjun D Desai Akshay S. Chaudhari S. Vasanawala Mert Pilanci John M. Pauly MedIm 68 8 0 21 Apr 2022
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging Kerstin Hammernik Thomas Kustner Burhaneddin Yaman Zhengnan Huang Daniel Rueckert Florian Knoll Mehmet Akçakaya PINN MedIm AI4CE 94 75 0 23 Mar 2022
Learning A 3D-CNN and Transformer Prior for Hyperspectral Image Super-Resolution Qing Ma Junjun Jiang Xianming Liu Jiayi Ma ViT 116 59 0 27 Nov 2021
Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration Mikael Le Pendu C. Guillemot 72 17 0 01 Oct 2021
A review and experimental evaluation of deep learning methods for MRI reconstruction Arghya Pal Yogesh Rathi 3DV 111 47 0 17 Sep 2021
Feasibility-based Fixed Point Networks Howard Heaton Samy Wu Fung A. Gibali W. Yin 57 26 0 29 Apr 2021
A Design Space Study for LISTA and Beyond Tianjian Meng Xiaohan Chen Yi Ding Zhangyang Wang 72 3 0 08 Apr 2021
Equivariant Imaging: Learning Beyond the Range Space Dongdong Chen Julián Tachella Mike E. Davies SSL 110 103 0 26 Mar 2021
Learning to Optimize: A Primer and A Benchmark Tianlong Chen Xiaohan Chen Wuyang Chen Howard Heaton Jialin Liu Zhangyang Wang W. Yin 266 237 0 23 Mar 2021
Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation Ce Wang Haimiao Zhang Qian Li Kun Shang Y. Lyu Bin Dong S. Kevin Zhou 128 14 0 09 Mar 2021
Deep Equilibrium Architectures for Inverse Problems in Imaging Davis Gilton Greg Ongie Rebecca Willett 103 183 0 16 Feb 2021
Non-Convex Compressed Sensing with Training Data G. Welper 65 1 0 20 Jan 2021
DAEs for Linear Inverse Problems: Improved Recovery with Provable Guarantees J. Dhaliwal Kyle Hambrook 118 0 0 13 Jan 2021
Phase Retrieval using Expectation Consistent Signal Recovery Algorithm based on Hypernetwork Chang-Jen Wang Chao-Kai Wen Shang-Ho S. Tsai Shi Jin Geoffrey Ye Li 60 5 0 12 Jan 2021
Convex Regularization Behind Neural Reconstruction Arda Sahiner Morteza Mardani Batu Mehmet Ozturkler Mert Pilanci John M. Pauly 67 25 0 09 Dec 2020
Model Adaptation for Inverse Problems in Imaging Davis Gilton Greg Ongie Rebecca Willett OOD MedIm 134 49 0 30 Nov 2020
TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problems Kaixuan Wei Angelica Aviles-Rivero Jingwei Liang Ying Fu Hua Huang Carola-Bibiane Schönlieb 74 35 0 18 Nov 2020
Convergence Acceleration via Chebyshev Step: Plausible Interpretation of Deep-Unfolded Gradient Descent Satoshi Takabe Tadashi Wadayama 61 10 0 26 Oct 2020
Unsupervised MRI Reconstruction with Generative Adversarial Networks Elizabeth K. Cole John M. Pauly S. Vasanawala Frank Ong GAN MedIm 62 51 0 29 Aug 2020
Neural Network-based Reconstruction in Compressed Sensing MRI Without Fully-sampled Training Data Alan Q. Wang Adrian Dalca M. Sabuncu 91 26 0 29 Jul 2020
FLOT: Scene Flow on Point Clouds Guided by Optimal Transport Gilles Puy Alexandre Boulch Renaud Marlet 3DPC OT 216 187 0 22 Jul 2020
Compressed Sensing via Measurement-Conditional Generative Models Kyungsu Kim J. H. Lee Eunho Yang GAN MedIm 69 3 0 02 Jul 2020
Compressive MR Fingerprinting reconstruction with Neural Proximal Gradient iterations Dongdong Chen Mike E. Davies Mohammad Golbabaee 66 16 0 27 Jun 2020
MetaInv-Net: Meta Inversion Network for Sparse View CT Image Reconstruction Haimiao Zhang Baodong Liu Hengyong Yu Bin Dong 82 63 0 30 May 2020
Deep Learning Techniques for Inverse Problems in Imaging Greg Ongie A. Jalal Christopher A. Metzler Richard G. Baraniuk A. Dimakis Rebecca Willett 128 537 0 12 May 2020
Learning Sampling and Model-Based Signal Recovery for Compressed Sensing MRI Iris A. M. Huijben Bastiaan S. Veeling Ruud J. G. van Sloun 90 33 0 22 Apr 2020
Analysis of Deep Complex-Valued Convolutional Neural Networks for MRI Reconstruction Elizabeth K. Cole Joseph Y. Cheng John M. Pauly S. Vasanawala 61 11 0 03 Apr 2020
Solving Inverse Problems with a Flow-based Noise Model Jay Whang Qi Lei A. Dimakis 132 39 0 18 Mar 2020