Deep Learning Techniques for Inverse Problems in Imaging

12 May 2020

Greg Ongie

A. Jalal

Christopher A. Metzler

Richard G. Baraniuk

A. Dimakis

Rebecca Willett

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Papers citing "Deep Learning Techniques for Inverse Problems in Imaging"

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Title
Deformation-Compensated Learning for Image Reconstruction without Ground Truth Weijie Gan Yu Sun C. Eldeniz Jiaming Liu Hongyu An Ulugbek S. Kamilov 107 14 0 12 Jul 2021
Solution of Physics-based Bayesian Inverse Problems with Deep Generative Priors Dhruv V. Patel Deep Ray Assad A. Oberai AI4CE 108 50 0 06 Jul 2021
Unsupervised Knowledge-Transfer for Learned Image Reconstruction Riccardo Barbano Ž. Kereta A. Hauptmann Simon Arridge Bangti Jin 95 11 0 06 Jul 2021
Fixed points of nonnegative neural networks Tomasz Piotrowski Renato L. G. Cavalcante Mateusz Gabor 256 8 0 30 Jun 2021
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors Zhaoqiang Liu Subhro Ghosh Jonathan Scarlett 112 19 0 29 Jun 2021
Data augmentation for deep learning based accelerated MRI reconstruction with limited data Zalan Fabian Reinhard Heckel Mahdi Soltanolkotabi OOD MedIm 96 55 0 28 Jun 2021
Instance-Optimal Compressed Sensing via Posterior Sampling A. Jalal Sushrut Karmalkar A. Dimakis Eric Price 129 55 0 21 Jun 2021
Learning the optimal Tikhonov regularizer for inverse problems Giovanni S. Alberti Ernesto De Vito Matti Lassas Luca Ratti Matteo Santacesaria 104 35 0 11 Jun 2021
Phase Retrieval using Single-Instance Deep Generative Prior Kshitij Tayal Raunak Manekar Zhong Zhuang David Yang Vipin Kumar F. Hofmann Ju Sun GAN 112 5 0 09 Jun 2021
Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition Jiaming Liu M. Salman Asif B. Wohlberg Ulugbek S. Kamilov 169 48 0 07 Jun 2021
OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression Nicola Bastianello Andrea Simonetto E. Dall’Anese 149 3 0 27 May 2021
A Geometry-Informed Deep Learning Framework for Ultra-Sparse 3D Tomographic Image Reconstruction Liyue Shen Wei Zhao D. Capaldi John M. Pauly Lei Xing 90 32 0 25 May 2021
Differentiable model-based adaptive optics for two-photon microscopy Ivan Vishniakou Johannes D. Seelig MedIm 46 4 0 29 Apr 2021
Fast ABC with joint generative modelling and subset simulation Eliane Maalouf D. Ginsbourger N. Linde 116 0 0 16 Apr 2021
CoPE: Conditional image generation using Polynomial Expansions Grigorios G. Chrysos Markos Georgopoulos Yannis Panagakis DiffM 90 12 0 11 Apr 2021
OGGN: A Novel Generalized Oracle Guided Generative Architecture for Modelling Inverse Function of Artificial Neural NetworksInternational Conference on Computer Vision and Image Processing (ICCVIP), 2025 Mohammad Aaftab Mansi Sharma 76 1 0 08 Apr 2021
Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems William Herzberg D. Rowe A. Hauptmann S. Hamilton GNN MedIm AI4CE 79 38 0 28 Mar 2021
Provable Compressed Sensing with Generative Priors via Langevin Dynamics Thanh V. Nguyen Gauri Jagatap Chinmay Hegde GAN 107 15 0 25 Feb 2021
Deep Equilibrium Architectures for Inverse Problems in Imaging Davis Gilton Greg Ongie Rebecca Willett 146 200 0 16 Feb 2021
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models Giannis Daras Joseph Dean A. Jalal A. Dimakis DRL 277 91 0 15 Feb 2021
An End-To-End-Trainable Iterative Network Architecture for Accelerated Radial Multi-Coil 2D Cine MR Image Reconstruction A. Kofler Markus Haltmeier T. Schaeffter C. Kolbitsch 3DV 117 25 0 01 Feb 2021
SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees Jiaming Liu Yu Sun Weijie Gan Xiaojian Xu B. Wohlberg Ulugbek S. Kamilov FedML MedIm 115 31 0 22 Jan 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 177 143 0 20 Jan 2021
Model-Based Deep Learning Nir Shlezinger Jay Whang Yonina C. Eldar A. Dimakis 254 367 0 15 Dec 2020
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging Hannah Lawrence David A. Barmherzig Henry Li Michael Eickenberg Marylou Gabrié 64 12 0 14 Dec 2020
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 183 33 0 11 Dec 2020
Convex Regularization Behind Neural Reconstruction Arda Sahiner Morteza Mardani Batu Mehmet Ozturkler Mert Pilanci John M. Pauly 109 25 0 09 Dec 2020
2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual Network Haoyu Wei Florian Schiffers Tobias Würfl Daming Shen Daniel Kim Aggelos K. Katsaggelos O. Cossairt 113 20 0 08 Dec 2020
Model Adaptation for Inverse Problems in Imaging Davis Gilton Greg Ongie Rebecca Willett OOD MedIm 188 49 0 30 Nov 2020
Joint Reconstruction and Calibration using Regularization by Denoising Mingyang Xie Yu Sun Jiaming Liu B. Wohlberg Ulugbek S. Kamilov 113 10 0 26 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 136 36 0 18 Nov 2020
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 95 114 0 09 Nov 2020
Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational ImagingAAAI Conference on Artificial Intelligence (AAAI), 2024 He Sun Katherine Bouman UQCV 111 78 0 27 Oct 2020
Learning an optimal PSF-pair for ultra-dense 3D localization microscopy E. Nehme Boris Ferdman Lucien E. Weiss Tal Naor Daniel Freedman T. Michaeli Y. Shechtman 122 5 0 29 Sep 2020
Fast ultrasonic imaging using end-to-end deep learning G. Pilikos L. Horchens K. Batenburg Tristan van Leeuwen F. Lucka MedIm 54 8 0 04 Sep 2020
Deep Networks and the Multiple Manifold ProblemInternational Conference on Learning Representations (ICLR), 2025 Sam Buchanan D. Gilboa John N. Wright 305 41 0 25 Aug 2020
Stochastic Multi-level Composition Optimization Algorithms with Level-Independent Convergence Rates Krishnakumar Balasubramanian Saeed Ghadimi A. Nguyen 220 34 0 24 Aug 2020
Deep learning for photoacoustic imaging: a survey Changchun Yang Hengrong Lan Feng Gao Fei Gao VLM MedIm 123 21 0 10 Aug 2020
Differentiable model-based adaptive optics with transmitted and reflected light Ivan Vishniakou Johannes D. Seelig MedIm 63 3 0 27 Jul 2020
Deep Learning Methods for Solving Linear Inverse Problems: Research Directions and Paradigms Yanna Bai Wei Chen Jie Chen Weisi Guo 145 73 0 27 Jul 2020
Robust Compressed Sensing using Generative ModelsNeural Information Processing Systems (NeurIPS), 2025 A. Jalal Liu Liu A. Dimakis Constantine Caramanis 171 43 0 16 Jun 2020
Supervised Learning of Sparsity-Promoting Regularizers for Denoising Michael T. McCann S. Ravishankar 71 8 0 09 Jun 2020
Constant-Expansion Suffices for Compressed Sensing with Generative PriorsNeural Information Processing Systems (NeurIPS), 2025 C. Daskalakis Dhruv Rohatgi Manolis Zampetakis 88 15 0 07 Jun 2020
Scalable Plug-and-Play ADMM with Convergence Guarantees Yu Sun Zihui Wu Xiaojian Xu B. Wohlberg Ulugbek S. Kamilov BDL 133 83 0 05 Jun 2020
How to do Physics-based Learning Michael R. Kellman Michael Lustig Laura Waller PINN AI4CE 26 2 0 27 May 2020
Inverse Problems, Deep Learning, and Symmetry Breaking Kshitij Tayal Chieh-Hsin Lai Vipin Kumar Ju Sun AI4CE 123 15 0 20 Mar 2020
Composing Normalizing Flows for Inverse Problems Jay Whang Erik M. Lindgren A. Dimakis TPM 153 53 0 26 Feb 2020
The troublesome kernel -- On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problems N. Gottschling Vegard Antun A. Hansen Ben Adcock 136 41 0 05 Jan 2020
Memory-efficient Learning for Large-scale Computational Imaging -- NeurIPS deep inverse workshop Michael R. Kellman Jonathan I. Tamir E. Bostan Michael Lustig Laura Waller SupR 129 60 0 11 Dec 2019
One-dimensional Deep Image Prior for Time Series Inverse Problems Sriram Ravula A. Dimakis 76 8 0 18 Apr 2019