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Information-Theoretic Lower Bounds for Compressive Sensing with Generative Models
IEEE Journal on Selected Areas in Information Theory (JSAIT), 2019
28 August 2019
Zhaoqiang Liu
Jonathan Scarlett
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Papers citing
"Information-Theoretic Lower Bounds for Compressive Sensing with Generative Models"
32 / 32 papers shown
Diffusion Model Based Signal Recovery Under 1-Bit Quantization
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Learning Single Index Models with Diffusion Priors
Anqi Tang
Youming Chen
Shuchen Xue
Zhaoqiang Liu
DiffM
311
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27 May 2025
Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models
Yang Zheng
Wen Li
Zhaoqiang Liu
453
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27 May 2025
Chasing Better Deep Image Priors between Over- and Under-parameterization
Qiming Wu
Xiaohan Chen
Lezhi Li
Zhangyang Wang
346
1
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31 Oct 2024
A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing
Neural Information Processing Systems (NeurIPS), 2023
Junren Chen
Jonathan Scarlett
Michael K. Ng
Zhaoqiang Liu
FedML
390
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25 Sep 2023
On the Fine-Grained Hardness of Inverting Generative Models
Feyza Duman Keles
Chinmay Hegde
207
1
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11 Sep 2023
Generalization analysis of an unfolding network for analysis-based Compressed Sensing
Applied and Computational Harmonic Analysis (ACHA), 2023
Vicky Kouni
Yannis Panagakis
MLT
385
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0
09 Mar 2023
MrSARP: A Hierarchical Deep Generative Prior for SAR Image Super-resolution
Tushar Agarwal
Nithin Sugavanam
Emre Ertin
GAN
271
2
0
30 Nov 2022
Misspecified Phase Retrieval with Generative Priors
Neural Information Processing Systems (NeurIPS), 2022
Zhaoqiang Liu
Xinshao Wang
Jiulong Liu
233
7
0
11 Oct 2022
Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Zhaoqiang Liu
J. Han
247
9
0
21 Sep 2022
A coherence parameter characterizing generative compressed sensing with Fourier measurements
IEEE Journal on Selected Areas in Information Theory (JSAIT), 2022
Aaron Berk
Simone Brugiapaglia
Babhru Joshi
Y. Plan
Matthew Scott
Özgür Yilmaz
311
10
0
19 Jul 2022
Theoretical Perspectives on Deep Learning Methods in Inverse Problems
IEEE Journal on Selected Areas in Information Theory (JSAIT), 2022
Jonathan Scarlett
Reinhard Heckel
M. Rodrigues
Paul Hand
Yonina C. Eldar
AI4CE
400
46
0
29 Jun 2022
Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems
Giannis Daras
Y. Dagan
A. Dimakis
C. Daskalakis
BDL
354
16
0
18 Jun 2022
Non-Iterative Recovery from Nonlinear Observations using Generative Models
Computer Vision and Pattern Recognition (CVPR), 2022
Jiulong Liu
Zhaoqiang Liu
355
13
0
31 May 2022
Generative Principal Component Analysis
International Conference on Learning Representations (ICLR), 2022
Zhaoqiang Liu
Jiulong Liu
Subhro Ghosh
Jun Han
Jonathan Scarlett
233
17
0
18 Mar 2022
Just Least Squares: Binary Compressive Sampling with Low Generative Intrinsic Dimension
Journal of Scientific Computing (J. Sci. Comput.), 2021
Yuling Jiao
Dingwei Li
Min Liu
Xiliang Lu
Yuanyuan Yang
213
3
0
29 Nov 2021
Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors
Information Theory Workshop (ITW), 2021
Zhaoqiang Liu
Subhro Ghosh
J. Han
Jonathan Scarlett
175
9
0
08 Aug 2021
Robust Compressed Sensing MRI with Deep Generative Priors
A. Jalal
Marius Arvinte
Giannis Daras
Eric Price
A. Dimakis
Jonathan I. Tamir
MedIm
390
427
0
03 Aug 2021
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors
Neural Information Processing Systems (NeurIPS), 2021
Zhaoqiang Liu
Subhro Ghosh
Jonathan Scarlett
269
21
0
29 Jun 2021
Instance-Optimal Compressed Sensing via Posterior Sampling
International Conference on Machine Learning (ICML), 2021
A. Jalal
Sushrut Karmalkar
A. Dimakis
Eric Price
224
62
0
21 Jun 2021
Learning Generative Prior with Latent Space Sparsity Constraints
Vinayak Killedar
P. Pokala
C. Seelamantula
260
3
0
25 May 2021
Provable Compressed Sensing with Generative Priors via Langevin Dynamics
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2021
Thanh V. Nguyen
Gauri Jagatap
Chinmay Hegde
GAN
209
17
0
25 Feb 2021
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
International Conference on Machine Learning (ICML), 2021
Giannis Daras
Joseph Dean
A. Jalal
A. Dimakis
DRL
398
99
0
15 Feb 2021
Subspace Embeddings Under Nonlinear Transformations
International Conference on Algorithmic Learning Theory (ALT), 2020
Aarshvi Gajjar
Cameron Musco
174
6
0
05 Oct 2020
The Generalized Lasso with Nonlinear Observations and Generative Priors
Zhaoqiang Liu
Jonathan Scarlett
337
29
0
22 Jun 2020
Robust Compressed Sensing using Generative Models
A. Jalal
Liu Liu
A. Dimakis
Constantine Caramanis
435
48
0
16 Jun 2020
Spectral DiffuserCam: lensless snapshot hyperspectral imaging with a spectral filter array
Kristina Monakhova
Kyrollos Yanny
Neerja Aggarwal
Laura Waller
165
148
0
15 Jun 2020
Solving Inverse Problems with a Flow-based Noise Model
International Conference on Machine Learning (ICML), 2020
Jay Whang
Qi Lei
A. Dimakis
401
42
0
18 Mar 2020
Composing Normalizing Flows for Inverse Problems
International Conference on Machine Learning (ICML), 2020
Jay Whang
Erik M. Lindgren
A. Dimakis
TPM
349
56
0
26 Feb 2020
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors
International Conference on Machine Learning (ICML), 2020
Zhaoqiang Liu
S. Gomes
Avtansh Tiwari
Jonathan Scarlett
272
30
0
05 Feb 2020
Lower Bounds for Compressed Sensing with Generative Models
Akshay Kamath
Sushrut Karmalkar
Eric Price
GAN
217
19
0
06 Dec 2019
Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis
Delin Qu
Xiaohan Wei
Zhuoran Yang
335
25
0
14 Aug 2019
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