Fetching the paper…
Reading the bibliography…
We examine the theoretical properties of enforcing priors provided by generative deep neural networks via empirical risk minimization.
A problem in geometric probability
James G Wendel · 1962
Earlier work this paper cites.
Some np-complete problems in quadratic and nonlinear programming
Katta G. Murty and Santosh N. Kabadi · 1987
Earlier work this paper cites.
Ten lectures on wavelets
Ingrid Daubechies · 1992
Earlier work this paper cites.
Stable signal recovery from incomplete and inaccurate measurements
Emmanuel J. Candès, Justin K. Romberg, and Terence Tao · 2006
Earlier work this paper cites.
For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution
David Donoho · 2006
Earlier work this paper cites.
Sparse mri: The application of compressed sensing for rapid mr imaging
Michael Lustig, David Donoho, and John M. Pauly · 2007
Earlier work this paper cites.
A simple proof of the restricted isometry property for random matrices
Richard Baraniuk, Mark Davenport, Ronald DeVore, and Michael Wakin · 2008
Earlier work this paper cites.
Exact matrix completion via convex optimization
Emmanuel J. Candès and Benjamin Recht · 2008
Earlier work this paper cites.
Counting faces of randomly projected polytopes when the projection radically lowers dimension
David Donoho and Jared Tanner · 2009
Earlier work this paper cites.
Pdbe: protein data bank in europe
Sameer Velankar, Christoph Best, B Beuth, CH Boutselakis, N Cobley, AW Sousa Da Silva, Dimitris Dimitropoulos, Adel Golovin, Miriam Hirshberg, Melford John, et al · 2009
Earlier work this paper cites.
Blind deconvolution using convex programming
Ali Ahmed, Benjamin Recht, and Justin K. Romberg · 2012
Earlier work this paper cites.
Group invariant scattering
S. Mallat · 2012
Earlier work this paper cites.
Introduction to the non-asymptotic analysis of random matrices
R. Vershynin · 2012
Earlier work this paper cites.
Phase retrieval via matrix completion
E. Candès, Y. Eldar, T. Strohmer, and V. Voroninski · 2013
Earlier work this paper cites.
Phaselift: Exact and stable signal recovery from magnitude measurements via convex programming
Emmanuel J Candès, Thomas Strohmer, and Vladislav Voroninski · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
Earlier work this paper cites.
Sparse signal recovery from quadratic measurements via convex programming
Xiaodong Li and Vladislav Voroninski · 2013
Earlier work this paper cites.
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
Earlier work this paper cites.
Generative adversarial networks
Ian J. Goodfellow, Jean Pouget-Abadie, Bing Mirza, Mehdi; Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Stochastic backpropagation and approximate inference in deep generative models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
Earlier work this paper cites.
Striving for simplicity: The all convolutional net
Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, and Martin A. Riedmiller · 2014
Earlier work this paper cites.
Why are deep nets reversible: A simple theory, with implications for training
Sanjeev Arora, Yingyu Liang, and Tengyu Ma · 2015
Earlier work this paper cites.
Phase retrieval via wirtinger flow: Theory and algorithms
Emmanuel J Candes, Xiaodong Li, and Mahdi Soltanolkotabi · 2015
Earlier work this paper cites.
Solving random quadratic systems of equations is nearly as easy as solving linear systems
Yuxin Chen and Emmanuel Candes · 2015
Earlier work this paper cites.
A deep learning approach to structured signal recovery
Ali Mousavi, Ankit B Patel, and Richard G Baraniuk · 2015
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
Cited alongside, same era.
On the low-rank approach for semidefinite programs arising in synchronization and community detection
Bandeira, Boumal, and Voroninski · 2016
Cited alongside, same era.
A nearly tight sum-of-squares lower bound for the planted clique problem
Boaz Barak, Samuel B Hopkins, Jonathan Kelner, Pravesh K Kothari, Ankur Moitra, and Aaron Potechin · 2016
Cited alongside, same era.
The projected power method: An efficient algorithm for joint alignment from pairwise differences
Yuxin Chen and Emmanuel Candes · 2016
Cited alongside, same era.
Deep neural networks with random gaussian weights: a universal classification strategy?
Precise recovery of latent vectors from generative adversarial networks
Zachary C Lipton and Subarna Tripathi · 2017
Closest in time.
High efficient optical remote sensing images acquisition for nano-satellite: reconstruction algorithms
Yang Liu, Feng Li, Lei Xin, Jie Fu, and Puming Huang · 2017
Closest in time.
Convolutional neural networks for non-iterative reconstruction of compressively sensed images
Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan Turaga, and Amit Ashok · 2017
Closest in time.
Cong Ma, Kaizheng Wang, Yuejie Chi, and Yuxin Chen · 2017
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Raja Giryes, Guillermo Sapiro, and Alexander M Bronstein · 2016
Cited alongside, same era.
Deep Learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 2016
Cited alongside, same era.
Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
Cited alongside, same era.
Photo-realistic single image super-resolution using a generative adversarial network
Christian Ledig, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, et al · 2016
Cited alongside, same era.
Rapid, robust, and reliable blind deconvolution via nonconvex optimization
Xiaodong Li, Shuyang Ling, Thomas Strohmer, and Ke Wei · 2016
Cited alongside, same era.
Image restoration using convolutional auto-encoders with symmetric skip connections. arxiv preprint
Xiao-Jiao Mao, Chunhua Shen, and Yu-Bin Yang · 2016
Cited alongside, same era.
Pixel recurrent neural networks
Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
Cited alongside, same era.
Amortised map inference for image super-resolution
Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, and Ferenc Huszár · 2016
Cited alongside, same era.
Dwarikanath Mahapatra · 2017
Closest in time.
Unsupervised reverse domain adaption for synthetic medical images via adversarial training
Faisal Mahmood, Richard Chen, and Nicholas J Durr · 2017
Closest in time.
Deep generative adversarial networks for compressed sensing automates mri
Morteza Mardani, Enhao Gong, Joseph Y Cheng, Shreyas Vasanawala, Greg Zaharchuk, Marcus Alley, Neil Thakur, Song Han, William Dally, John M Pauly, et al · 2017
Closest in time.
Morteza Mardani, Hatef Monajemi, Vardan Papyan, Shreyas Vasanawala, David Donoho, and John Pauly · 2017
Closest in time.
A well-tempered landscape for non-convex robust subspace recovery
Tyler Maunu, Teng Zhang, and Gilad Lerman · 2017
Closest in time.
Adversarial training and dilated convolutions for brain mri segmentation
Pim Moeskops, Mitko Veta, Maxime W Lafarge, Koen AJ Eppenhof, and Josien PW Pluim · 2017
Closest in time.
Learning to invert: Signal recovery via deep convolutional networks
Ali Mousavi and Richard G Baraniuk · 2017
Closest in time.
Medical image synthesis with context-aware generative adversarial networks
Dong Nie, Roger Trullo, Jun Lian, Caroline Petitjean, Su Ruan, Qian Wang, and Dinggang Shen · 2017
Closest in time.
Compressed sensing mri reconstruction with cyclic loss in generative adversarial networks
Tran Minh Quan, Thanh Nguyen-Duc, and Won-Ki Jeong · 2017
Closest in time.
Real-time adaptive image compression
Oren Rippel and Lubomir Bourdev · 2017
Closest in time.
Deep learning microscopy
Yair Rivenson, Zoltán Göröcs, Harun Günaydin, Yibo Zhang, Hongda Wang, and Aydogan Ozcan · 2017
Closest in time.
Pixeldefend: Leveraging generative models to understand and defend against adversarial examples
Yang Song, Taesup Kim, Sebastian Nowozin, Stefano Ermon, and Nate Kushman · 2017
Closest in time.
Generative adversarial networks for noise reduction in low-dose ct
Jelmer M Wolterink, Tim Leiner, Max A Viergever, and Ivana Išgum · 2017
Closest in time.
Segan: Adversarial network with multi-scale l _ 1 l\_1 loss for medical image segmentation
Yuan Xue, Tao Xu, Han Zhang, Rodney Long, and Xiaolei Huang · 2017
Closest in time.
Dagan: Deep de-aliasing generative adversarial networks for fast compressed sensing mri reconstruction
Guang Yang, Simiao Yu, Hao Dong, Greg Slabaugh, Pier Luigi Dragotti, Xujiong Ye, Fangde Liu, Simon Arridge, Jennifer Keegan, Yike Guo, et al · 2017
Closest in time.
Semantic image inpainting with deep generative models
Raymond A Yeh, Chen Chen, Teck Yian Lim, Alexander G Schwing, Mark Hasegawa-Johnson, and Minh N Do · 2017
Closest in time.
Adversarial examples: Attacks and defenses for deep learning
Xiaoyong Yuan, Pan He, Qile Zhu, Rajendra Rana Bhat, and Xiaolin Li · 2017
Closest in time.
Learned primal-dual reconstruction
Jonas Adler and Ozan Öktem · 2018
Closest in time.
Threat of adversarial attacks on deep learning in computer vision: A survey
Naveed Akhtar and Ajmal Mian · 2018
Closest in time.
Using deep neural networks for inverse problems in imaging: Beyond analytical methods
Alice Lucas, Michael Iliadis, Rafael Molina, and Aggelos K Katsaggelos · 2018
Closest in time.