Learning to Invert: Signal Recovery via Deep Convolutional Networks

14 January 2017

Richard G. Baraniuk

Papers citing "Learning to Invert: Signal Recovery via Deep Convolutional Networks"

20 / 20 papers shown

Title
Comprehensive Examination of Unrolled Networks for Solving Linear Inverse Problems Eric Chen Xi Chen A. Maleki S. Jalali 33 0 0 08 Jan 2025
Deep Physics-Guided Unrolling Generalization for Compressed Sensing Bin Chen Jie Song Jingfen Xie Jian Andrew Zhang AI4CE 16 14 0 18 Jul 2023
Content-aware Scalable Deep Compressed Sensing Bin Chen Jian Andrew Zhang 21 54 0 19 Jul 2022
Survey of Deep Learning Methods for Inverse Problems S. Kamyab Zihreh Azimifar Rasool Sabzi Paul Fieguth 21 3 0 07 Nov 2021
Jointly Sparse Signal Recovery and Support Recovery via Deep Learning with Applications in MIMO-based Grant-Free Random Access Ying Cui Shuaichao Li Wanqing Zhang 16 61 0 05 Aug 2020
FLOT: Scene Flow on Point Clouds Guided by Optimal Transport Gilles Puy Alexandre Boulch Renaud Marlet 3DPC OT 127 183 0 22 Jul 2020
Image Deconvolution via Noise-Tolerant Self-Supervised Inversion H. Kobayashi A. Solak Joshua D. Batson Loic A. Royer 14 13 0 11 Jun 2020
Deep Learning Techniques for Inverse Problems in Imaging Greg Ongie A. Jalal Christopher A. Metzler Richard G. Baraniuk A. Dimakis Rebecca Willett 11 519 0 12 May 2020
Plug-and-Play Algorithms for Large-scale Snapshot Compressive Imaging Xin Yuan Yang Liu J. Suo Qionghai Dai 18 178 0 30 Mar 2020
Inverse Problems, Deep Learning, and Symmetry Breaking Kshitij Tayal Chieh-Hsin Lai Vipin Kumar Ju Sun AI4CE 72 15 0 20 Mar 2020
Multi-Channel Deep Networks for Block-Based Image Compressive Sensing Siwang Zhou Yan He Yonghe Liu Chengqing Li Jianming Zhang 16 112 0 28 Aug 2019
Deep Representation with ReLU Neural Networks Andreas Heinecke W. Hwang 28 0 0 29 Mar 2019
Algorithmic Aspects of Inverse Problems Using Generative Models C. Hegde GAN 25 21 0 08 Oct 2018
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling Shanshan Wu A. Dimakis Sujay Sanghavi Felix X. Yu D. Holtmann-Rice Dmitry Storcheus Afshin Rostamizadeh Sanjiv Kumar SSL 17 53 0 26 Jun 2018
Solving Linear Inverse Problems Using GAN Priors: An Algorithm with Provable Guarantees Viraj Shah C. Hegde GAN 13 161 0 23 Feb 2018
Full Image Recover for Block-Based Compressive Sensing Xuemei Xie Chenye Wang Jiang Du Guangming Shi 25 16 0 01 Feb 2018
MoDL: Model Based Deep Learning Architecture for Inverse Problems H. Aggarwal M. Mani M. Jacob 46 997 0 07 Dec 2017
Convolutional Neural Networks for Non-iterative Reconstruction of Compressively Sensed Images Suhas Lohit K. Kulkarni Ronan Kerviche P. Turaga A. Ashok 9 114 0 15 Aug 2017
Deep Learning-Based Communication Over the Air Sebastian Dörner Sebastian Cammerer J. Hoydis S. Brink 11 702 0 11 Jul 2017
An Introduction to Deep Learning for the Physical Layer Tim O'Shea J. Hoydis AI4CE 89 2,171 0 02 Feb 2017