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Tensor Monte Carlo: particle methods for the GPU era

22 June 2018

Papers citing "Tensor Monte Carlo: particle methods for the GPU era"

26 / 26 papers shown

Title
Pyro: Deep Universal Probabilistic Programming Eli Bingham Jonathan P. Chen M. Jankowiak F. Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman BDL GP 158 1,057 0 18 Oct 2018
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives George Tucker Dieterich Lawson S. Gu Chris J. Maddison BDL 74 110 0 09 Oct 2018
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow T. Le Adam R. Kosiorek N. Siddharth Yee Whye Teh Frank Wood BDL 56 23 0 26 May 2018
Tighter Variational Bounds are Not Necessarily Better Tom Rainforth Adam R. Kosiorek T. Le Chris J. Maddison Maximilian Igl Frank Wood Yee Whye Teh DRL 174 198 0 13 Feb 2018
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation Will Grathwohl Dami Choi Yuhuai Wu Geoffrey Roeder David Duvenaud 116 300 0 31 Oct 2017
Variational Sequential Monte Carlo C. A. Naesseth Scott W. Linderman Rajesh Ranganath David M. Blei BDL 279 214 0 31 May 2017
Auto-Encoding Sequential Monte Carlo T. Le Maximilian Igl Tom Rainforth Tom Jin Frank Wood BDL DRL 321 152 0 29 May 2017
Filtering Variational Objectives Chris J. Maddison Dieterich Lawson George Tucker N. Heess Mohammad Norouzi A. Mnih Arnaud Doucet Yee Whye Teh FedML 249 210 0 25 May 2017
Reinterpreting Importance-Weighted Autoencoders Chris Cremer Q. Morris David Duvenaud BDL FAtt 111 94 0 10 Apr 2017
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference Geoffrey Roeder Yuhuai Wu David Duvenaud BDL 142 202 0 27 Mar 2017
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 363 5,388 0 03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables Chris J. Maddison A. Mnih Yee Whye Teh BDL 200 2,541 0 02 Nov 2016
Composing graphical models with neural networks for structured representations and fast inference Matthew J. Johnson David Duvenaud Alexander B. Wiltschko S. R. Datta Ryan P. Adams BDL OCL 92 485 0 20 Mar 2016
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks Tim Salimans Diederik P. Kingma ODL 196 1,945 0 25 Feb 2016
Variational inference for Monte Carlo objectives A. Mnih Danilo Jimenez Rezende DRL BDL 171 291 0 22 Feb 2016
Ladder Variational Autoencoders C. Sønderby T. Raiko Lars Maaløe Søren Kaae Sønderby Ole Winther BDL DRL 99 915 0 06 Feb 2016
The sample size required in importance sampling S. Chatterjee P. Diaconis 147 191 0 04 Nov 2015
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 280 1,246 0 01 Sep 2015
A New Approach to Probabilistic Programming Inference Frank Wood Jan-Willem van de Meent Vikash K. Mansinghka 65 347 0 03 Jul 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
Reweighted Wake-Sleep J. Bornschein Yoshua Bengio BDL 120 183 0 11 Jun 2014
Venture: a higher-order probabilistic programming platform with programmable inference Vikash K. Mansinghka Daniel Selsam Yura N. Perov 76 256 0 01 Apr 2014
Black Box Variational Inference Rajesh Ranganath S. Gerrish David M. Blei DRL BDL 150 1,167 0 31 Dec 2013
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 458 16,922 0 20 Dec 2013
Extending Factor Graphs so as to Unify Directed and Undirected Graphical Models B. Frey 79 87 0 19 Oct 2012
Curse-of-dimensionality revisited: Collapse of the particle filter in very large scale systems T. Bengtsson Peter J. Bickel Bo Li 133 421 0 20 May 2008