NICE: Non-linear Independent Components Estimation

30 October 2014

Papers citing "NICE: Non-linear Independent Components Estimation"

50 / 514 papers shown

Title
MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks Animesh Karnewar Oliver Wang GAN 16 50 0 14 Mar 2019
Hierarchical Autoregressive Image Models with Auxiliary Decoders J. Fauw Sander Dieleman Karen Simonyan GAN 30 37 0 06 Mar 2019
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation Manoj Kumar Mohammad Babaeizadeh D. Erhan Chelsea Finn Sergey Levine Laurent Dinh Durk Kingma VGen 25 131 0 04 Mar 2019
Video Extrapolation with an Invertible Linear Embedding Robert Pottorff Jared Nielsen David Wingate 30 5 0 01 Mar 2019
ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs A. Gholami Kurt Keutzer George Biros 30 166 0 27 Feb 2019
Hybrid Models with Deep and Invertible Features Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan BDL DRL 22 99 0 07 Feb 2019
Improving Evolutionary Strategies with Generative Neural Networks Louis Faury Clément Calauzènes Olivier Fercoq Syrine Krichene 27 12 0 31 Jan 2019
Emerging Convolutions for Generative Normalizing Flows Emiel Hoogeboom Rianne van den Berg Max Welling DRL 24 98 0 30 Jan 2019
Deep Generative Learning via Variational Gradient Flow Yuan Gao Yuling Jiao Yang Wang Yao Wang Can Yang Shunkang Zhang 27 36 0 24 Jan 2019
Coupling the reduced-order model and the generative model for an importance sampling estimator Xiaoliang Wan Shuangqing Wei 16 10 0 23 Jan 2019
Understanding the (un)interpretability of natural image distributions using generative models Ryen Krusinga Sohil Shah Matthias Zwicker Tom Goldstein David Jacobs DiffM FAtt GAN 28 11 0 06 Jan 2019
StoryGAN: A Sequential Conditional GAN for Story Visualization Yitong Li Zhe Gan Yelong Shen Jingjing Liu Yu Cheng Yuexin Wu Lawrence Carin David Carlson Jianfeng Gao 41 226 0 06 Dec 2018
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging Seong Jae Hwang Zirui Tao Won Hwa Kim Vikas Singh MedIm 33 12 0 24 Nov 2018
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 37 618 0 02 Nov 2018
WaveGlow: A Flow-based Generative Network for Speech Synthesis R. Prenger Rafael Valle Bryan Catanzaro 87 1,023 0 31 Oct 2018
Towards Principled Uncertainty Estimation for Deep Neural Networks Richard E. Harang Ethan M. Rudd BDL UQCV 30 6 0 29 Oct 2018
Metropolis-Hastings view on variational inference and adversarial training Kirill Neklyudov Evgenii Egorov Pavel Shvechikov Dmitry Vetrov GAN 29 13 0 16 Oct 2018
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection Hyun-Jae Choi Eric Jang Alexander A. Alemi OODD 20 82 0 02 Oct 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl Ricky T. Q. Chen J. Bettencourt Ilya Sutskever David Duvenaud DRL 17 851 0 02 Oct 2018
Boosting Trust Region Policy Optimization by Normalizing Flows Policy Yunhao Tang Shipra Agrawal TPM 39 29 0 27 Sep 2018
Monge-Ampère Flow for Generative Modeling Linfeng Zhang E. Weinan Lei Wang DRL 28 62 0 26 Sep 2018
Learning deep representations by mutual information estimation and maximization R. Devon Hjelm A. Fedorov Samuel Lavoie-Marchildon Karan Grewal Phil Bachman Adam Trischler Yoshua Bengio SSL DRL 84 2,640 0 20 Aug 2018
Analyzing Inverse Problems with Invertible Neural Networks Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert D. Rahner E. Pellegrini R. Klessen Lena Maier-Hein Carsten Rother Ullrich Kothe 21 484 0 14 Aug 2018
A Review of Learning with Deep Generative Models from Perspective of Graphical Modeling Zhijian Ou 31 16 0 05 Aug 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 55 3,085 0 09 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 110 4,960 0 19 Jun 2018
Meta-Learning for Stochastic Gradient MCMC Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato BDL 38 44 0 12 Jun 2018
Mining gold from implicit models to improve likelihood-free inference Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer AI4CE TPM 38 181 0 30 May 2018
Semi-Implicit Variational Inference Mingzhang Yin Mingyuan Zhou BDL 39 121 0 28 May 2018
Neural Autoregressive Flows Chin-Wei Huang David M. Krueger Alexandre Lacoste Aaron Courville DRL AI4CE 31 433 0 03 Apr 2018
Sylvester Normalizing Flows for Variational Inference Rianne van den Berg Leonard Hasenclever Jakub M. Tomczak Max Welling BDL DRL 18 249 0 15 Mar 2018
Quantitatively Evaluating GANs With Divergences Proposed for Training Daniel Jiwoong Im He Ma Graham W. Taylor K. Branson EGVM 19 69 0 02 Mar 2018
Disentangling the independently controllable factors of variation by interacting with the world Valentin Thomas Emmanuel Bengio W. Fedus Jules Pondard Philippe Beaudoin Hugo Larochelle Joelle Pineau Doina Precup Yoshua Bengio DRL CoGe CML 24 61 0 26 Feb 2018
Is Generator Conditioning Causally Related to GAN Performance? Augustus Odena Jacob Buckman Catherine Olsson Tom B. Brown C. Olah Colin Raffel Ian Goodfellow AI4CE 35 112 0 23 Feb 2018
BRUNO: A Deep Recurrent Model for Exchangeable Data I. Korshunova Jonas Degrave Ferenc Huszár Y. Gal Arthur Gretton J. Dambre BDL 24 33 0 21 Feb 2018
i-RevNet: Deep Invertible Networks J. Jacobsen A. Smeulders Edouard Oyallon 52 333 0 20 Feb 2018
Neural Network Renormalization Group Shuo-Hui Li Lei Wang BDL DRL 37 125 0 08 Feb 2018
Transformation Autoregressive Networks Junier B. Oliva Kumar Avinava Dubey Manzil Zaheer Barnabás Póczós Ruslan Salakhutdinov Eric Xing J. Schneider OOD 28 86 0 30 Jan 2018
Parallel WaveNet: Fast High-Fidelity Speech Synthesis Aaron van den Oord Yazhe Li Igor Babuschkin Karen Simonyan Oriol Vinyals ... Alex Graves Helen King T. Walters Dan Belov Demis Hassabis 38 856 0 28 Nov 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Learning Independent Features with Adversarial Nets for Non-linear ICA Philemon Brakel Yoshua Bengio OOD CML 27 93 0 13 Oct 2017
Learnable Explicit Density for Continuous Latent Space and Variational Inference Chin-Wei Huang Ahmed Touati Laurent Dinh M. Drozdzal Mohammad Havaei Laurent Charlin Aaron Courville BDL DRL 45 28 0 06 Oct 2017
Reversible Architectures for Arbitrarily Deep Residual Neural Networks B. Chang Lili Meng E. Haber Lars Ruthotto David Begert E. Holtham AI4CE 36 261 0 12 Sep 2017
Unsupervised Generative Modeling Using Matrix Product States Zhaoyu Han Jun Wang H. Fan Lei Wang Pan Zhang 27 268 0 06 Sep 2017
A-NICE-MC: Adversarial Training for MCMC Jiaming Song Shengjia Zhao Stefano Ermon BDL OOD 32 109 0 23 Jun 2017
Variational Sequential Monte Carlo C. A. Naesseth Scott W. Linderman Rajesh Ranganath David M. Blei BDL 41 214 0 31 May 2017
Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models Aditya Grover Manik Dhar Stefano Ermon GAN 39 24 0 24 May 2017
Sharp Minima Can Generalize For Deep Nets Laurent Dinh Razvan Pascanu Samy Bengio Yoshua Bengio ODL 46 758 0 15 Mar 2017
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications Tim Salimans A. Karpathy Xi Chen Diederik P. Kingma 19 933 0 19 Jan 2017
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks L. Mescheder Sebastian Nowozin Andreas Geiger GAN BDL 49 525 0 17 Jan 2017