ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2303.05582
  4. Cited By
Generalization analysis of an unfolding network for analysis-based Compressed Sensing
v1v2v3 (latest)

Generalization analysis of an unfolding network for analysis-based Compressed Sensing

9 March 2023
Vicky Kouni
Yannis Panagakis
    MLT
ArXiv (abs)PDFHTML

Papers citing "Generalization analysis of an unfolding network for analysis-based Compressed Sensing"

19 / 19 papers shown
Title
Theoretical Perspectives on Deep Learning Methods in Inverse Problems
Theoretical Perspectives on Deep Learning Methods in Inverse Problems
Jonathan Scarlett
Reinhard Heckel
M. Rodrigues
Paul Hand
Yonina C. Eldar
AI4CE
110
32
0
29 Jun 2022
Deep Generalized Unfolding Networks for Image Restoration
Deep Generalized Unfolding Networks for Image Restoration
Chong Mou
Qian Wang
Jian Zhang
109
196
0
28 Apr 2022
Memory-augmented Deep Unfolding Network for Guided Image
  Super-resolution
Memory-augmented Deep Unfolding Network for Guided Image Super-resolution
Man Zhou
Keyu Yan
Jin-shan Pan
Wenqi Ren
Qiaokang Xie
Xiangyong Cao
GANSupR
74
65
0
12 Feb 2022
ADMM-DAD net: a deep unfolding network for analysis compressed sensing
ADMM-DAD net: a deep unfolding network for analysis compressed sensing
Vicky Kouni
Georgios Paraskevopoulos
Holger Rauhut
G. C. Alexandropoulos
107
19
0
13 Oct 2021
LADMM-Net: An Unrolled Deep Network For Spectral Image Fusion From
  Compressive Data
LADMM-Net: An Unrolled Deep Network For Spectral Image Fusion From Compressive Data
J. Ramírez
J. I. M. Torre
Henry Arguello
90
26
0
01 Mar 2021
Compressive Sensing and Neural Networks from a Statistical Learning
  Perspective
Compressive Sensing and Neural Networks from a Statistical Learning Perspective
Arash Behboodi
Holger Rauhut
Ekkehard Schnoor
103
19
0
29 Oct 2020
Iterative Algorithm Induced Deep-Unfolding Neural Networks: Precoding
  Design for Multiuser MIMO Systems
Iterative Algorithm Induced Deep-Unfolding Neural Networks: Precoding Design for Multiuser MIMO Systems
Qiyu Hu
Yunlong Cai
Qingjiang Shi
Kaidi Xu
Guanding Yu
Z. Ding
48
175
0
15 Jun 2020
Interpretable Deep Recurrent Neural Networks via Unfolding Reweighted
  $\ell_1$-$\ell_1$ Minimization: Architecture Design and Generalization
  Analysis
Interpretable Deep Recurrent Neural Networks via Unfolding Reweighted ℓ1\ell_1ℓ1​-ℓ1\ell_1ℓ1​ Minimization: Architecture Design and Generalization Analysis
Huynh Van Luong
Boris Joukovsky
Nikos Deligiannis
44
4
0
18 Mar 2020
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal
  and Image Processing
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
V. Monga
Yuelong Li
Yonina C. Eldar
130
1,027
0
22 Dec 2019
Information-Theoretic Lower Bounds for Compressive Sensing with
  Generative Models
Information-Theoretic Lower Bounds for Compressive Sensing with Generative Models
Zhaoqiang Liu
Jonathan Scarlett
110
41
0
28 Aug 2019
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep
  Neural Networks
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks
Yuan Cao
Quanquan Gu
MLTAI4CE
131
392
0
30 May 2019
Fast Compressive Sensing Recovery Using Generative Models with
  Structured Latent Variables
Fast Compressive Sensing Recovery Using Generative Models with Structured Latent Variables
Shaojie Xu
Sihan Zeng
Justin Romberg
GANDiffM
85
16
0
19 Feb 2019
Stronger generalization bounds for deep nets via a compression approach
Stronger generalization bounds for deep nets via a compression approach
Sanjeev Arora
Rong Ge
Behnam Neyshabur
Yi Zhang
MLTAI4CE
168
643
0
14 Feb 2018
Spectrally-normalized margin bounds for neural networks
Spectrally-normalized margin bounds for neural networks
Peter L. Bartlett
Dylan J. Foster
Matus Telgarsky
ODL
350
1,225
0
26 Jun 2017
A vector-contraction inequality for Rademacher complexities
A vector-contraction inequality for Rademacher complexities
Andreas Maurer
103
261
0
01 May 2016
Dictionary Learning for Blind One Bit Compressed Sensing
Dictionary Learning for Blind One Bit Compressed Sensing
H. Zayyani
Mehdi Korki
F. Marvasti
50
43
0
30 Aug 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
535
18,688
0
06 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.5K
150,661
0
22 Dec 2014
Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures
Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures
J. Hershey
Jonathan Le Roux
F. Weninger
BDL
229
433
0
09 Sep 2014
1