Auto-Encoding Variational Bayes

20 December 2013

Papers citing "Auto-Encoding Variational Bayes"

42 / 3,542 papers shown

Title
Deep Kalman Filters Rahul G. Krishnan Uri Shalit David Sontag BDL AI4TS 36 371 0 16 Nov 2015
How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary? Ferenc Huszár OOD DiffM GAN 28 296 0 16 Nov 2015
Black-box $α$ -divergence Minimization José Miguel Hernández-Lobato Yingzhen Li Mark Rowland Daniel Hernández-Lobato T. Bui Richard Turner 23 137 0 10 Nov 2015
Generating Images from Captions with Attention Elman Mansimov Emilio Parisotto Jimmy Lei Ba Ruslan Salakhutdinov VLM 55 450 0 09 Nov 2015
Hierarchical Variational Models Rajesh Ranganath Dustin Tran David M. Blei DRL VLM 28 335 0 07 Nov 2015
The Variational Fair Autoencoder Christos Louizos Kevin Swersky Yujia Li Max Welling R. Zemel DRL 51 632 0 03 Nov 2015
Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions Mohammad Emtiyaz Khan Reza Babanezhad Wu Lin Mark Schmidt Masashi Sugiyama 33 49 0 31 Oct 2015
Learning Continuous Control Policies by Stochastic Value Gradients N. Heess Greg Wayne David Silver Timothy Lillicrap Yuval Tassa Tom Erez 66 558 0 30 Oct 2015
Learning FRAME Models Using CNN Filters Yang Lu Song-Chun Zhu Ying Nian Wu GAN 28 66 0 28 Sep 2015
Deep Temporal Sigmoid Belief Networks for Sequence Modeling Zhe Gan Chunyuan Li Ricardo Henao David Carlson Lawrence Carin BDL 32 85 0 23 Sep 2015
Learning Wake-Sleep Recurrent Attention Models Jimmy Ba Roger C. Grosse Ruslan Salakhutdinov B. Frey BDL 32 65 0 22 Sep 2015
Fast Second-Order Stochastic Backpropagation for Variational Inference Kai Fan Ziteng Wang J. Beck James T. Kwok Katherine A. Heller ODL BDL DRL 23 45 0 09 Sep 2015
Stochastic gradient variational Bayes for gamma approximating distributions David A. Knowles BDL 30 50 0 04 Sep 2015
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 101 1,236 0 01 Sep 2015
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks Emily L. Denton Soumith Chintala Arthur Szlam Rob Fergus GAN 47 2,241 0 18 Jun 2015
Gradient Estimation Using Stochastic Computation Graphs John Schulman N. Heess T. Weber Pieter Abbeel OffRL 41 391 0 17 Jun 2015
Bayesian representation learning with oracle constraints Theofanis Karaletsos Serge J. Belongie Gunnar Rätsch BDL 35 92 0 16 Jun 2015
Data Generation as Sequential Decision Making Philip Bachman Doina Precup 30 57 0 10 Jun 2015
Automatic Variational Inference in Stan A. Kucukelbir Rajesh Ranganath Andrew Gelman David M. Blei BDL 37 232 0 10 Jun 2015
Neural Adaptive Sequential Monte Carlo S. Gu Zoubin Ghahramani Richard Turner BDL 24 145 0 10 Jun 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 69 1,494 0 08 Jun 2015
A Recurrent Latent Variable Model for Sequential Data Junyoung Chung Kyle Kastner Laurent Dinh Kratarth Goel Aaron Courville Yoshua Bengio DRL BDL 42 1,244 0 07 Jun 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 213 745 0 06 Jun 2015
Dropout as a Bayesian Approximation: Appendix Y. Gal Zoubin Ghahramani BDL 24 64 0 06 Jun 2015
Automatic Relevance Determination For Deep Generative Models Theofanis Karaletsos Gunnar Rätsch 33 8 0 28 May 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 110 4,114 0 21 May 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 38 1,874 0 20 May 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 115 6,650 0 12 Mar 2015
Deep Convolutional Inverse Graphics Network Tejas D. Kulkarni William F. Whitney Pushmeet Kohli J. Tenenbaum DRL BDL 50 929 0 11 Mar 2015
Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data Y. Gal Yutian Chen Zoubin Ghahramani SyDa 45 41 0 07 Mar 2015
Automatic differentiation in machine learning: a survey A. G. Baydin Barak A. Pearlmutter Alexey Radul J. Siskind PINN AI4CE ODL 75 2,754 0 20 Feb 2015
DRAW: A Recurrent Neural Network For Image Generation Karol Gregor Ivo Danihelka Alex Graves Danilo Jimenez Rezende Daan Wierstra GAN DRL 79 1,957 0 16 Feb 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention Ke Xu Jimmy Ba Ryan Kiros Kyunghyun Cho Aaron Courville Ruslan Salakhutdinov R. Zemel Yoshua Bengio DiffM 163 10,018 0 10 Feb 2015
Generative Class-conditional Autoencoders Jan Rudy Graham W. Taylor DRL 31 7 0 22 Dec 2014
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 95 149,056 0 22 Dec 2014
Learning Stochastic Recurrent Networks Justin Bayer Christian Osendorfer BDL 40 273 0 27 Nov 2014
Variational Inference for Uncertainty on the Inputs of Gaussian Process Models Andreas C. Damianou Michalis K. Titsias Neil D. Lawrence 47 25 0 08 Sep 2014
How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation Yoshua Bengio 53 181 0 29 Jul 2014
Techniques for Learning Binary Stochastic Feedforward Neural Networks T. Raiko Mathias Berglund Guillaume Alain Laurent Dinh BDL 65 126 0 11 Jun 2014
Structured Stochastic Variational Inference Matthew D. Hoffman David M. Blei BDL 42 87 0 16 Apr 2014
Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets Diederik P. Kingma Max Welling BDL 44 61 0 03 Feb 2014
On Using Control Variates with Stochastic Approximation for Variational Bayes and its Connection to Stochastic Linear Regression Tim Salimans David A. Knowles BDL 48 33 0 06 Jan 2014