Variational Sequential Monte Carlo

31 May 2017

Papers citing "Variational Sequential Monte Carlo"

41 / 141 papers shown

Title
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation Justin Domke Daniel Sheldon 26 18 0 24 Jun 2019
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting Aditya Grover Jiaming Song Alekh Agarwal Kenneth Tran Ashish Kapoor Eric Horvitz Stefano Ermon 26 123 0 23 Jun 2019
Reweighted Expectation Maximization Adji Bousso Dieng John Paisley VLM DRL 14 17 0 13 Jun 2019
Coupled Variational Recurrent Collaborative Filtering Qingquan Song Shiyu Chang Xia Hu BDL 6 9 0 11 Jun 2019
Streaming Variational Monte Carlo Yuan Zhao Josue Nassar I. Jordan M. Bugallo Il Memming Park BDL 34 21 0 04 Jun 2019
Particle Filter Recurrent Neural Networks Xiao Ma Peter Karkus David Hsu Wee Sun Lee 14 82 0 30 May 2019
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces P. Becker Harit Pandya Gregor H. W. Gebhardt Cheng Zhao James Taylor Gerhard Neumann BDL 24 94 0 17 May 2019
A Contrastive Divergence for Combining Variational Inference and MCMC Francisco J. R. Ruiz Michalis K. Titsias BDL 19 60 0 10 May 2019
Importance Weighted Hierarchical Variational Inference Artem Sobolev Dmitry Vetrov BDL 16 26 0 08 May 2019
Elements of Sequential Monte Carlo C. A. Naesseth Fredrik Lindsten Thomas B. Schon 26 95 0 12 Mar 2019
Quasi-Bayes properties of a recursive procedure for mixtures S. Fortini Sonia Petrone 14 2 0 27 Feb 2019
Particle Flow Bayes' Rule Xinshi Chen H. Dai Le Song 22 9 0 02 Feb 2019
Stochastic Gradient MCMC for Nonlinear State Space Models Christopher Aicher Srshti Putcha Christopher Nemeth Paul Fearnhead E. Fox BDL 28 7 0 29 Jan 2019
Learning Nonlinear State Space Models with Hamiltonian Sequential Monte Carlo Sampler Duo Xu 29 2 0 03 Jan 2019
A Tutorial on Deep Latent Variable Models of Natural Language Yoon Kim Sam Wiseman Alexander M. Rush BDL VLM 30 42 0 17 Dec 2018
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Pierre-Alexandre Mattei J. Frellsen SyDa 25 45 0 06 Dec 2018
Black-Box Autoregressive Density Estimation for State-Space Models Tom Ryder Andrew Golightly A. Mcgough D. Prangle BDL 19 6 0 20 Nov 2018
A General Method for Amortizing Variational Filtering Joseph Marino Milan Cvitkovic Yisong Yue 27 34 0 13 Nov 2018
The Variational Deficiency Bottleneck P. Banerjee Guido Montúfar 15 7 0 27 Oct 2018
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives George Tucker Dieterich Lawson S. Gu Chris J. Maddison BDL 19 110 0 09 Oct 2018
An Introduction to Probabilistic Programming Jan-Willem van de Meent Brooks Paige Hongseok Yang Frank Wood GP 30 196 0 27 Sep 2018
Bayesian dynamic variable selection in high dimensions Gary Koop Dimitris Korobilis 16 38 0 09 Sep 2018
Importance Weighting and Variational Inference Justin Domke Daniel Sheldon 17 107 0 27 Aug 2018
Unbiased Implicit Variational Inference Michalis K. Titsias Francisco J. R. Ruiz BDL 24 52 0 06 Aug 2018
Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems Jung-Su Ha Young-Jin Park Hyeok-Joo Chae Soon-Seo Park Han-Lim Choi BDL 19 26 0 05 Jul 2018
Tensor Monte Carlo: particle methods for the GPU era Laurence Aitchison BDL DRL 27 13 0 22 Jun 2018
Deep State Space Models for Unconditional Word Generation Florian Schmidt Thomas Hofmann 25 14 0 12 Jun 2018
Deep Variational Reinforcement Learning for POMDPs Maximilian Igl L. Zintgraf T. Le Frank Wood Shimon Whiteson BDL OffRL 21 259 0 06 Jun 2018
Reparameterization Gradient for Non-differentiable Models Wonyeol Lee Hangyeol Yu Hongseok Yang DRL 25 30 0 01 Jun 2018
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers Marcel Hirt P. Dellaportas BDL 20 10 0 23 May 2018
Particle Filter Networks with Application to Visual Localization Peter Karkus David Hsu Wee Sun Lee 3DPC 27 117 0 23 May 2018
Variational Rejection Sampling Aditya Grover Ramki Gummadi Miguel Lazaro-Gredilla Dale Schuurmans Stefano Ermon BDL 26 32 0 05 Apr 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 34 197 0 13 Feb 2018
Faithful Inversion of Generative Models for Effective Amortized Inference Stefan Webb Adam Goliñski R. Zinkov Siddharth Narayanaswamy Tom Rainforth Yee Whye Teh Frank Wood TPM 51 46 0 01 Dec 2017
State Space LSTM Models with Particle MCMC Inference Xun Zheng Manzil Zaheer Amr Ahmed Yali Wang Eric Xing Alex Smola BDL 30 46 0 30 Nov 2017
On Nesting Monte Carlo Estimators Tom Rainforth R. Cornish Hongseok Yang Andrew Warrington Frank Wood 23 131 0 18 Sep 2017
Auto-Encoding Sequential Monte Carlo T. Le Maximilian Igl Tom Rainforth Tom Jin Frank Wood BDL DRL 26 151 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 22 210 0 25 May 2017
AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms Marco F. Cusumano-Towner Vikash K. Mansinghka 22 17 0 19 May 2017
Reinterpreting Importance-Weighted Autoencoders Chris Cremer Q. Morris David Duvenaud BDL FAtt 19 94 0 10 Apr 2017
Variational Particle Approximations A. Saeedi Tejas D. Kulkarni Vikash K. Mansinghka S. Gershman 87 60 0 24 Feb 2014