Auto-Encoding Variational Bayes

20 December 2013

Papers citing "Auto-Encoding Variational Bayes"

50 / 3,300 papers shown

Title
Memory-based control with recurrent neural networks N. Heess Jonathan J. Hunt Timothy Lillicrap David Silver 29 301 0 14 Dec 2015
Black box variational inference for state space models Evan Archer Il Memming Park Lars Buesing John P. Cunningham Liam Paninski BDL 37 160 0 23 Nov 2015
Recurrent Gaussian Processes C. L. C. Mattos Zhenwen Dai Andreas C. Damianou Jeremy Forth G. Barreto Neil D. Lawrence BDL 32 75 0 20 Nov 2015
The Variational Gaussian Process Dustin Tran Rajesh Ranganath David M. Blei BDL 37 184 0 20 Nov 2015
Variational Auto-encoded Deep Gaussian Processes Zhenwen Dai Andreas C. Damianou Javier I. González Neil D. Lawrence BDL 24 131 0 19 Nov 2015
Towards Principled Unsupervised Learning Ilya Sutskever Rafal Jozefowicz Karol Gregor Danilo Jimenez Rezende Timothy Lillicrap Oriol Vinyals OOD SSL 27 49 0 19 Nov 2015
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford Luke Metz Soumith Chintala GAN OOD 125 13,936 0 19 Nov 2015
Learning to Generate Images with Perceptual Similarity Metrics Jake C. Snell Karl Ridgeway Renjie Liao Brett D. Roads Michael C. Mozer R. Zemel EGVM 27 176 0 19 Nov 2015
Generating Sentences from a Continuous Space Samuel R. Bowman Luke Vilnis Oriol Vinyals Andrew M. Dai Rafal Jozefowicz Samy Bengio DRL 34 2,343 0 19 Nov 2015
Neural Variational Inference for Text Processing Yishu Miao Lei Yu Phil Blunsom VLM DRL 28 616 0 19 Nov 2015
Super-Resolution with Deep Convolutional Sufficient Statistics Joan Bruna Pablo Sprechmann Yann LeCun SupR 25 323 0 18 Nov 2015
MuProp: Unbiased Backpropagation for Stochastic Neural Networks S. Gu Sergey Levine Ilya Sutskever A. Mnih BDL 13 143 0 16 Nov 2015
Deep Kalman Filters Rahul G. Krishnan Uri Shalit David Sontag BDL AI4TS 33 370 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 52 450 0 09 Nov 2015
Hierarchical Variational Models Rajesh Ranganath Dustin Tran David M. Blei DRL VLM 25 335 0 07 Nov 2015
The Variational Fair Autoencoder Christos Louizos Kevin Swersky Yujia Li Max Welling R. Zemel DRL 24 632 0 03 Nov 2015
Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions Mohammad Emtiyaz Khan Reza Babanezhad Wu Lin Mark W. 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 19 557 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 29 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
Stochastic gradient variational Bayes for gamma approximating distributions David A. Knowles BDL 24 50 0 04 Sep 2015
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 23 1,236 0 01 Sep 2015
Gradient Estimation Using Stochastic Computation Graphs John Schulman N. Heess T. Weber Pieter Abbeel OffRL 41 389 0 17 Jun 2015
Bayesian representation learning with oracle constraints Theofanis Karaletsos Serge J. Belongie Gunnar Rätsch BDL 32 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 31 232 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 1,493 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 1,242 0 07 Jun 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 205 745 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 77 4,109 0 21 May 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 29 1,872 0 20 May 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 94 6,635 0 12 Mar 2015
Deep Convolutional Inverse Graphics Network Tejas D. Kulkarni William F. Whitney Pushmeet Kohli J. Tenenbaum DRL BDL 44 929 0 11 Mar 2015
Automatic differentiation in machine learning: a survey A. G. Baydin Barak A. Pearlmutter Alexey Radul J. Siskind PINN AI4CE ODL 75 2,751 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 52 1,955 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 133 10,008 0 10 Feb 2015
Generative Class-conditional Autoencoders Jan Rudy Graham W. Taylor DRL 25 7 0 22 Dec 2014
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 29 148,989 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 44 25 0 08 Sep 2014
How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation Yoshua Bengio 47 181 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 34 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 40 33 0 06 Jan 2014