Deep Unsupervised Learning using Nonequilibrium Thermodynamics

12 March 2015

Jascha Narain Sohl-Dickstein

Papers citing "Deep Unsupervised Learning using Nonequilibrium Thermodynamics"

24 / 1,374 papers shown

Title
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey Konstantinos Benidis Syama Sundar Rangapuram Valentin Flunkert Bernie Wang Danielle C. Maddix ... David Salinas Lorenzo Stella François-Xavier Aubet Laurent Callot Tim Januschowski AI4TS 25 176 0 21 Apr 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 Feb 2020
Hidden Unit Specialization in Layered Neural Networks: ReLU vs. Sigmoidal Activation Elisa Oostwal Michiel Straat Michael Biehl MLT 56 55 0 16 Oct 2019
Neural Joint Source-Channel Coding Kristy Choi Kedar Tatwawadi Aditya Grover Tsachy Weissman Stefano Ermon 13 38 0 19 Nov 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 44 191 0 02 Oct 2018
Monge-Ampère Flow for Generative Modeling Linfeng Zhang E. Weinan Lei Wang DRL 12 62 0 26 Sep 2018
Variational Autoencoder with Arbitrary Conditioning Oleg Ivanov Michael Figurnov Dmitry Vetrov BDL DRL 19 145 0 06 Jun 2018
Transportation analysis of denoising autoencoders: a novel method for analyzing deep neural networks Sho Sonoda Noboru Murata 16 8 0 12 Dec 2017
Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net Anirudh Goyal Nan Rosemary Ke Surya Ganguli Yoshua Bengio DiffM 35 55 0 07 Nov 2017
Continuous-Time Flows for Efficient Inference and Density Estimation Changyou Chen Chunyuan Li Liquan Chen Wenlin Wang Yunchen Pu Lawrence Carin TPM 46 57 0 04 Sep 2017
Optimizing the Latent Space of Generative Networks Piotr Bojanowski Armand Joulin David Lopez-Paz Arthur Szlam GAN 27 412 0 18 Jul 2017
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications Tim Salimans A. Karpathy Xi Chen Diederik P. Kingma 19 931 0 19 Jan 2017
An Architecture for Deep, Hierarchical Generative Models Philip Bachman AI4CE BDL 33 53 0 08 Dec 2016
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks Emily L. Denton Sam Gross Rob Fergus GAN 27 150 0 19 Nov 2016
Variational Lossy Autoencoder Xi Chen Diederik P. Kingma Tim Salimans Yan Duan Prafulla Dhariwal John Schulman Ilya Sutskever Pieter Abbeel DRL SSL GAN 47 671 0 08 Nov 2016
Unrolled Generative Adversarial Networks Luke Metz Ben Poole David Pfau Jascha Narain Sohl-Dickstein GAN 59 1,001 0 07 Nov 2016
Coupled Generative Adversarial Networks Ming Liu Oncel Tuzel OOD GAN 22 1,622 0 24 Jun 2016
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 55 1,797 0 15 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 97 3,647 0 26 May 2016
Pixel-Level Domain Transfer Donggeun Yoo Namil Kim Sunggyun Park Anthony S. Paek In So Kweon GAN 14 315 0 24 Mar 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 272 2,552 0 25 Jan 2016
Super-Resolution with Deep Convolutional Sufficient Statistics Joan Bruna Pablo Sprechmann Yann LeCun SupR 25 323 0 18 Nov 2015
Data Generation as Sequential Decision Making Philip Bachman Doina Precup 22 57 0 10 Jun 2015
Automatic Relevance Determination For Deep Generative Models Theofanis Karaletsos Gunnar Rätsch 33 8 0 28 May 2015