Fetching the paper…
Reading the bibliography…
We study the problem of inverting a deep generative model with ReLU activations.
Combining geometry and combinatorics: A unified approach to sparse signal recovery
Radu Berinde, Anna C Gilbert, Piotr Indyk, Howard Karloff, and Martin J Strauss · 2008
Earlier work this paper cites.
Smallest singular value of a random rectangular matrix
Mark Rudelson and Roman Vershynin · 2009
Earlier work this paper cites.
Lower bounds on the column sparsity of sparse recovery matrices
Mergen Nachin · 2010
Earlier work this paper cites.
Matrix computations
Gene H Golub and Charles F Van Loan · 2012
Earlier work this paper cites.
On model-based rip-1 matrices
Piotr Indyk and Ilya Razenshteyn · 2013
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Restricted isometry property for general p-norms
Zeyuan Allen-Zhu, Rati Gelashvili, and Ilya Razenshteyn · 2016
Earlier work this paper cites.
Compressed sensing using generative models
Ashish Bora, Ajil Jalal, Eric Price, and Alexandros G Dimakis · 2017
Earlier work this paper cites.
Inference in deep networks in high dimensions
Alyson K Fletcher and Sundeep Rangan · 2017
Cited alongside, same era.
Global guarantees for enforcing deep generative priors by empirical risk
Paul Hand and Vladislav Voroninski · 2017
Cited alongside, same era.
The little engine that could: Regularization by denoising (red)
Yaniv Romano, Michael Elad, and Peyman Milanfar · 2017
Cited alongside, same era.
Modeling sparse deviations for compressed sensing using generative models
Manik Dhar, Aditya Grover, and Stefano Ermon · 2018
Cited alongside, same era.
Aditya Grover and Stefano Ermon · 2018
Deep denoising: Rate-optimal recovery of structured signals with a deep prior
Reinhard Heckel, Wen Huang, Paul Hand, and Vladislav Voroninski · 2018
Later among the works it cites.
A provably convergent scheme for compressive sensing under random generative priors
Wen Huang, Paul Hand, Reinhard Heckel, and Vladislav Voroninski · 2018
Later among the works it cites.
Neural proximal gradient descent for compressive imaging
Morteza Mardani, Qingyun Sun, Shreyas Vasawanala, Vardan Papyan, Hatef Monajemi, John Pauly, and David Donoho · 2018
Later among the works it cites.
Sunlayer: Stable denoising with generative networks
Dustin G Mixon and Soledad Villar · 2018
Later among the works it cites.
Solving linear inverse problems using gan priors: An algorithm with provable guarantees
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Deep mesh projectors for inverse problems
Sidharth Gupta, Konik Kothari, Maarten V de Hoop, and Ivan Dokmanić · 2018
Cited alongside, same era.
Phase retrieval under a generative prior
Paul Hand, Oscar Leong, and Vlad Voroninski · 2018
Cited alongside, same era.
Deep decoder: Concise image representations from untrained non-convolutional networks
Reinhard Heckel and Paul Hand · 2018
Cited alongside, same era.
Viraj Shah and Chinmay Hegde · 2018
Later among the works it cites.
Correction by projection: Denoising images with generative adversarial networks
Subarna Tripathi, Zachary C Lipton, and Truong Q Nguyen · 2018
Later among the works it cites.
The spiked matrix model with generative priors
Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, and Lenka Zdeborová · 2019
Closest in time.
Asymptotics of map inference in deep networks
Parthe Pandit, Mojtaba Sahraee, Sundeep Rangan, and Alyson K Fletcher · 2019
Closest in time.