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Sandwiching the marginal likelihood using bidirectional Monte Carlo

Sandwiching the marginal likelihood using bidirectional Monte Carlo

8 November 2015
Roger C. Grosse
Zoubin Ghahramani
Ryan P. Adams
ArXiv (abs)PDFHTML

Papers citing "Sandwiching the marginal likelihood using bidirectional Monte Carlo"

32 / 32 papers shown
Title
Optimization of Annealed Importance Sampling Hyperparameters
Optimization of Annealed Importance Sampling Hyperparameters
Shirin Goshtasbpour
Fernando Perez-Cruz
58
1
0
27 Sep 2022
Bounding Evidence and Estimating Log-Likelihood in VAE
Bounding Evidence and Estimating Log-Likelihood in VAE
Lukasz Struski
Marcin Mazur
Pawel Batorski
Przemysław Spurek
Jacek Tabor
98
3
0
19 Jun 2022
Guaranteed Bounds for Posterior Inference in Universal Probabilistic
  Programming
Guaranteed Bounds for Posterior Inference in Universal Probabilistic Programming
Raven Beutner
Luke Ong
Fabian Zaiser
69
12
0
06 Apr 2022
Estimators of Entropy and Information via Inference in Probabilistic
  Models
Estimators of Entropy and Information via Inference in Probabilistic Models
Feras A. Saad
Marco F. Cusumano-Towner
Vikash K. Mansinghka
63
4
0
24 Feb 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Sanae Lotfi
Pavel Izmailov
Gregory W. Benton
Micah Goldblum
A. Wilson
UQCVBDL
149
58
0
23 Feb 2022
BAM: Bayes with Adaptive Memory
BAM: Bayes with Adaptive Memory
Josue Nassar
Jennifer Brennan
Ben Evans
Kendall Lowrey
CLLKELM
53
1
0
04 Feb 2022
Surrogate Likelihoods for Variational Annealed Importance Sampling
Surrogate Likelihoods for Variational Annealed Importance Sampling
M. Jankowiak
Du Phan
BDL
85
13
0
22 Dec 2021
Differentiable Annealed Importance Sampling and the Perils of Gradient
  Noise
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise
Guodong Zhang
Kyle Hsu
Jianing Li
Chelsea Finn
Roger C. Grosse
87
40
0
21 Jul 2021
MCMC Variational Inference via Uncorrected Hamiltonian Annealing
MCMC Variational Inference via Uncorrected Hamiltonian Annealing
Tomas Geffner
Justin Domke
95
36
0
08 Jul 2021
q-Paths: Generalizing the Geometric Annealing Path using Power Means
q-Paths: Generalizing the Geometric Annealing Path using Power Means
Vaden Masrani
Rob Brekelmans
T. Bui
Frank Nielsen
Aram Galstyan
Greg Ver Steeg
Frank Wood
266
16
0
01 Jul 2021
Monte Carlo Variational Auto-Encoders
Monte Carlo Variational Auto-Encoders
Achille Thin
Nikita Kotelevskii
Arnaud Doucet
Alain Durmus
Eric Moulines
Maxim Panov
BDLDRL
70
45
0
30 Jun 2021
An Easy to Interpret Diagnostic for Approximate Inference: Symmetric
  Divergence Over Simulations
An Easy to Interpret Diagnostic for Approximate Inference: Symmetric Divergence Over Simulations
Justin Domke
22
9
0
25 Feb 2021
Annealed Importance Sampling with q-Paths
Annealed Importance Sampling with q-Paths
Rob Brekelmans
Vaden Masrani
T. Bui
Frank Wood
Aram Galstyan
Greg Ver Steeg
Frank Nielsen
61
10
0
14 Dec 2020
Evaluating Lossy Compression Rates of Deep Generative Models
Evaluating Lossy Compression Rates of Deep Generative Models
Sicong Huang
Alireza Makhzani
Yanshuai Cao
Roger C. Grosse
EGVMDRL
91
27
0
15 Aug 2020
Differentiable Molecular Simulations for Control and Learning
Differentiable Molecular Simulations for Control and Learning
Wujie Wang
Simon Axelrod
Rafael Gómez-Bombarelli
AI4CE
196
49
0
27 Feb 2020
Normalizing Constant Estimation with Gaussianized Bridge Sampling
Normalizing Constant Estimation with Gaussianized Bridge Sampling
He Jia
U. Seljak
71
9
0
12 Dec 2019
Importance Weighted Hierarchical Variational Inference
Importance Weighted Hierarchical Variational Inference
Artem Sobolev
Dmitry Vetrov
BDL
79
29
0
08 May 2019
Elements of Sequential Monte Carlo
Elements of Sequential Monte Carlo
C. A. Naesseth
Fredrik Lindsten
Thomas B. Schon
75
97
0
12 Mar 2019
Asymptotic Consistency of $α-$Rényi-Approximate Posteriors
Asymptotic Consistency of α−α-α−Rényi-Approximate Posteriors
Prateek Jaiswal
Vinayak A. Rao
Harsha Honnappa
85
12
0
05 Feb 2019
Gaussian Process Behaviour in Wide Deep Neural Networks
Gaussian Process Behaviour in Wide Deep Neural Networks
A. G. Matthews
Mark Rowland
Jiri Hron
Richard Turner
Zoubin Ghahramani
BDL
195
561
0
30 Apr 2018
Inference Suboptimality in Variational Autoencoders
Inference Suboptimality in Variational Autoencoders
Chris Cremer
Xuechen Li
David Duvenaud
DRLBDL
137
283
0
10 Jan 2018
Filtering Variational Objectives
Filtering Variational Objectives
Chris J. Maddison
Dieterich Lawson
George Tucker
N. Heess
Mohammad Norouzi
A. Mnih
Arnaud Doucet
Yee Whye Teh
FedML
260
210
0
25 May 2017
AIDE: An algorithm for measuring the accuracy of probabilistic inference
  algorithms
AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms
Marco F. Cusumano-Towner
Vikash K. Mansinghka
102
18
0
19 May 2017
Continuously tempered Hamiltonian Monte Carlo
Continuously tempered Hamiltonian Monte Carlo
Matthew M. Graham
Amos J. Storkey
74
26
0
11 Apr 2017
Approximate Inference with Amortised MCMC
Approximate Inference with Amortised MCMC
Yingzhen Li
Richard Turner
Qiang Liu
BDL
96
62
0
27 Feb 2017
Adversarial Message Passing For Graphical Models
Adversarial Message Passing For Graphical Models
Theofanis Karaletsos
GAN
85
29
0
15 Dec 2016
Measuring the non-asymptotic convergence of sequential Monte Carlo
  samplers using probabilistic programming
Measuring the non-asymptotic convergence of sequential Monte Carlo samplers using probabilistic programming
Marco F. Cusumano-Towner
Vikash K. Mansinghka
45
3
0
07 Dec 2016
On the Quantitative Analysis of Decoder-Based Generative Models
On the Quantitative Analysis of Decoder-Based Generative Models
Yuhuai Wu
Yuri Burda
Ruslan Salakhutdinov
Roger C. Grosse
GAN
129
223
0
14 Nov 2016
Variational Inference via $χ$-Upper Bound Minimization
Variational Inference via χχχ-Upper Bound Minimization
Adji Bousso Dieng
Dustin Tran
Rajesh Ranganath
John Paisley
David M. Blei
BDL
144
35
0
01 Nov 2016
Measuring the reliability of MCMC inference with bidirectional Monte
  Carlo
Measuring the reliability of MCMC inference with bidirectional Monte Carlo
Roger C. Grosse
Siddharth Ancha
Daniel M. Roy
123
27
0
07 Jun 2016
Partition Functions from Rao-Blackwellized Tempered Sampling
Partition Functions from Rao-Blackwellized Tempered Sampling
David Carlson
Patrick Stinson
Ari Pakman
Liam Paninski
120
13
0
07 Mar 2016
Patterns of Scalable Bayesian Inference
Patterns of Scalable Bayesian Inference
E. Angelino
Matthew J. Johnson
Ryan P. Adams
107
87
0
16 Feb 2016
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