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1705.11140
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Variational Sequential Monte Carlo
International Conference on Artificial Intelligence and Statistics (AISTATS), 2017
31 May 2017
C. A. Naesseth
Scott W. Linderman
Rajesh Ranganath
David M. Blei
BDL
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Papers citing
"Variational Sequential Monte Carlo"
47 / 147 papers shown
Energy-Inspired Models: Learning with Sampler-Induced Distributions
Neural Information Processing Systems (NeurIPS), 2019
Dieterich Lawson
George Tucker
Bo Dai
Rajesh Ranganath
298
32
0
31 Oct 2019
Customizing Sequence Generation with Multi-Task Dynamical Systems
Alex Bird
Christopher K. I. Williams
AI4CE
180
11
0
11 Oct 2019
DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs
International Joint Conference on Artificial Intelligence (IJCAI), 2019
Yunbo Wang
Bo Liu
Jiajun Wu
Yuke Zhu
Simon S. Du
Fei-Fei Li
Joshua B. Tenenbaum
160
7
0
28 Sep 2019
Particle Smoothing Variational Objectives
A. Moretti
Zizhao Wang
Luhuan Wu
Iddo Drori
I. Pe’er
151
10
0
20 Sep 2019
On importance-weighted autoencoders
Axel Finke
Alexandre Hoang Thiery
180
2
0
24 Jul 2019
Vector Quantized Bayesian Neural Network Inference for Data Streams
AAAI Conference on Artificial Intelligence (AAAI), 2019
Namuk Park
Taekyu Lee
Songkuk Kim
MQ
165
11
0
12 Jul 2019
The Thermodynamic Variational Objective
Neural Information Processing Systems (NeurIPS), 2019
Vaden Masrani
T. Le
Frank Wood
695
50
0
28 Jun 2019
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation
Neural Information Processing Systems (NeurIPS), 2019
Justin Domke
Daniel Sheldon
303
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
193
130
0
23 Jun 2019
Reweighted Expectation Maximization
Adji Bousso Dieng
John Paisley
VLM
DRL
168
17
0
13 Jun 2019
Coupled Variational Recurrent Collaborative Filtering
Knowledge Discovery and Data Mining (KDD), 2019
Qingquan Song
Shiyu Chang
Helen Zhou
BDL
162
9
0
11 Jun 2019
Streaming Variational Monte Carlo
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
Yuan Zhao
Josue Nassar
I. Jordan
M. Bugallo
Il Memming Park
BDL
503
21
0
04 Jun 2019
Particle Filter Recurrent Neural Networks
AAAI Conference on Artificial Intelligence (AAAI), 2019
Xiao Ma
Peter Karkus
David Hsu
Wee Sun Lee
289
90
0
30 May 2019
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
International Conference on Machine Learning (ICML), 2019
P. Becker
Harit Pandya
Gregor H. W. Gebhardt
Cheng Zhao
James Taylor
Gerhard Neumann
BDL
209
110
0
17 May 2019
A Contrastive Divergence for Combining Variational Inference and MCMC
International Conference on Machine Learning (ICML), 2019
Francisco J. R. Ruiz
Michalis K. Titsias
BDL
225
61
0
10 May 2019
Importance Weighted Hierarchical Variational Inference
Neural Information Processing Systems (NeurIPS), 2019
Artem Sobolev
Dmitry Vetrov
BDL
157
31
0
08 May 2019
Elements of Sequential Monte Carlo
C. A. Naesseth
Fredrik Lindsten
Thomas B. Schon
221
106
0
12 Mar 2019
Quasi-Bayes properties of a recursive procedure for mixtures
S. Fortini
Sonia Petrone
82
3
0
27 Feb 2019
Particle Flow Bayes' Rule
International Conference on Machine Learning (ICML), 2019
Xinshi Chen
H. Dai
Le Song
276
10
0
02 Feb 2019
Stochastic Gradient MCMC for Nonlinear State Space Models
Bayesian Analysis (BA), 2019
Christopher Aicher
Srshti Putcha
Christopher Nemeth
Paul Fearnhead
E. Fox
BDL
356
8
0
29 Jan 2019
Learning Nonlinear State Space Models with Hamiltonian Sequential Monte Carlo Sampler
Duo Xu
143
2
0
03 Jan 2019
A Tutorial on Deep Latent Variable Models of Natural Language
Yoon Kim
Sam Wiseman
Alexander M. Rush
BDL
VLM
270
45
0
17 Dec 2018
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data
Pierre-Alexandre Mattei
J. Frellsen
SyDa
141
48
0
06 Dec 2018
Black-Box Autoregressive Density Estimation for State-Space Models
Tom Ryder
Andrew Golightly
A. Mcgough
D. Prangle
BDL
166
6
0
20 Nov 2018
A General Method for Amortizing Variational Filtering
Joseph Marino
Milan Cvitkovic
Yisong Yue
192
35
0
13 Nov 2018
The Variational Deficiency Bottleneck
P. Banerjee
Guido Montúfar
267
7
0
27 Oct 2018
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
George Tucker
Dieterich Lawson
S. Gu
Chris J. Maddison
BDL
227
111
0
09 Oct 2018
An Introduction to Probabilistic Programming
Jan-Willem van de Meent
Brooks Paige
Hongseok Yang
Frank Wood
GP
285
217
0
27 Sep 2018
Bayesian dynamic variable selection in high dimensions
Gary Koop
Dimitris Korobilis
164
47
0
09 Sep 2018
Importance Weighting and Variational Inference
Justin Domke
Daniel Sheldon
248
110
0
27 Aug 2018
Unbiased Implicit Variational Inference
Michalis K. Titsias
Francisco J. R. Ruiz
BDL
377
59
0
06 Aug 2018
Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems
Journal of Statistical Mechanics: Theory and Experiment (JSTAT), 2018
Jung-Su Ha
Young-Jin Park
Hyeok-Joo Chae
Soon-Seo Park
Han-Lim Choi
BDL
204
27
0
05 Jul 2018
Tensor Monte Carlo: particle methods for the GPU era
Laurence Aitchison
BDL
DRL
251
14
0
22 Jun 2018
Deep State Space Models for Unconditional Word Generation
Florian Schmidt
Thomas Hofmann
146
16
0
12 Jun 2018
Deep Variational Reinforcement Learning for POMDPs
Maximilian Igl
L. Zintgraf
T. Le
Frank Wood
Shimon Whiteson
BDL
OffRL
321
284
0
06 Jun 2018
Reparameterization Gradient for Non-differentiable Models
Wonyeol Lee
Hangyeol Yu
Hongseok Yang
DRL
322
36
0
01 Jun 2018
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers
Marcel Hirt
P. Dellaportas
BDL
219
11
0
23 May 2018
Particle Filter Networks with Application to Visual Localization
Peter Karkus
David Hsu
Wee Sun Lee
3DPC
248
139
0
23 May 2018
Variational Rejection Sampling
Aditya Grover
Ramki Gummadi
Miguel Lazaro-Gredilla
Dale Schuurmans
Stefano Ermon
BDL
197
35
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
446
205
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
199
52
0
01 Dec 2017
State Space LSTM Models with Particle MCMC Inference
Xun Zheng
Manzil Zaheer
Amr Ahmed
Longji Xu
Eric Xing
Alex Smola
BDL
119
47
0
30 Nov 2017
On Nesting Monte Carlo Estimators
Tom Rainforth
R. Cornish
Hongseok Yang
Andrew Warrington
Frank Wood
365
147
0
18 Sep 2017
Auto-Encoding Sequential Monte Carlo
T. Le
Maximilian Igl
Tom Rainforth
Tom Jin
Frank Wood
BDL
DRL
480
159
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
469
219
0
25 May 2017
AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms
Marco F. Cusumano-Towner
Vikash K. Mansinghka
284
20
0
19 May 2017
Reinterpreting Importance-Weighted Autoencoders
Chris Cremer
Q. Morris
David Duvenaud
BDL
FAtt
194
95
0
10 Apr 2017
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