ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1905.04062
  4. Cited By
A Contrastive Divergence for Combining Variational Inference and MCMC

A Contrastive Divergence for Combining Variational Inference and MCMC

10 May 2019
Francisco J. R. Ruiz
Michalis K. Titsias
    BDL
ArXivPDFHTML

Papers citing "A Contrastive Divergence for Combining Variational Inference and MCMC"

19 / 19 papers shown
Title
Bayesian Computation in Deep Learning
Bayesian Computation in Deep Learning
Wenlong Chen
Bolian Li
Ruqi Zhang
Yingzhen Li
BDL
75
0
0
25 Feb 2025
Reparameterized Variational Rejection Sampling
Reparameterized Variational Rejection Sampling
M. Jankowiak
Du Phan
DRL
BDL
24
1
0
26 Sep 2023
Markov Chain Score Ascent: A Unifying Framework of Variational Inference
  with Markovian Gradients
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients
Kyurae Kim
Jisu Oh
Jacob R. Gardner
Adji Bousso Dieng
Hongseok Kim
BDL
29
8
0
13 Jun 2022
PAVI: Plate-Amortized Variational Inference
PAVI: Plate-Amortized Variational Inference
Louis Rouillard
Thomas Moreau
Demian Wassermann
25
1
0
10 Jun 2022
Parallel Tempering With a Variational Reference
Parallel Tempering With a Variational Reference
Nikola Surjanovic
Saifuddin Syed
Alexandre Bouchard-Coté
Trevor Campbell
28
11
0
31 May 2022
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC
Anna Kuzina
Max Welling
Jakub M. Tomczak
AAML
DRL
31
12
0
18 Mar 2022
Optimal Regret Is Achievable with Bounded Approximate Inference Error:
  An Enhanced Bayesian Upper Confidence Bound Framework
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework
Ziyi Huang
H. Lam
A. Meisami
Haofeng Zhang
36
4
0
31 Jan 2022
Surrogate Likelihoods for Variational Annealed Importance Sampling
Surrogate Likelihoods for Variational Annealed Importance Sampling
M. Jankowiak
Du Phan
BDL
35
13
0
22 Dec 2021
MCMC Variational Inference via Uncorrected Hamiltonian Annealing
MCMC Variational Inference via Uncorrected Hamiltonian Annealing
Tomas Geffner
Justin Domke
25
34
0
08 Jul 2021
Variational Refinement for Importance Sampling Using the Forward
  Kullback-Leibler Divergence
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence
Ghassen Jerfel
S. Wang
Clara Fannjiang
Katherine A. Heller
Yi Ma
Michael I. Jordan
BDL
14
40
0
30 Jun 2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a
  Geometry-Based Variational Autoencoder
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder
Clément Chadebec
Elina Thibeau-Sutre
Ninon Burgos
S. Allassonnière
36
61
0
30 Apr 2021
Stein Variational Gradient Descent: many-particle and long-time
  asymptotics
Stein Variational Gradient Descent: many-particle and long-time asymptotics
Nikolas Nusken
D. M. Renger
27
22
0
25 Feb 2021
Improved Contrastive Divergence Training of Energy Based Models
Improved Contrastive Divergence Training of Energy Based Models
Yilun Du
Shuang Li
J. Tenenbaum
Igor Mordatch
41
138
0
02 Dec 2020
Geometry-Aware Hamiltonian Variational Auto-Encoder
Geometry-Aware Hamiltonian Variational Auto-Encoder
Clément Chadebec
Clément Mantoux
S. Allassonnière
DRL
22
15
0
22 Oct 2020
VarGrad: A Low-Variance Gradient Estimator for Variational Inference
VarGrad: A Low-Variance Gradient Estimator for Variational Inference
Lorenz Richter
Ayman Boustati
Nikolas Nusken
Francisco J. R. Ruiz
Ömer Deniz Akyildiz
DRL
136
48
0
20 Oct 2020
All in the Exponential Family: Bregman Duality in Thermodynamic
  Variational Inference
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference
Rob Brekelmans
Vaden Masrani
Frank D. Wood
Greg Ver Steeg
Aram Galstyan
6
16
0
01 Jul 2020
Markovian Score Climbing: Variational Inference with KL(p||q)
Markovian Score Climbing: Variational Inference with KL(p||q)
C. A. Naesseth
Fredrik Lindsten
David M. Blei
121
54
0
23 Mar 2020
A bi-partite generative model framework for analyzing and simulating
  large scale multiple discrete-continuous travel behaviour data
A bi-partite generative model framework for analyzing and simulating large scale multiple discrete-continuous travel behaviour data
Melvin Wong
Bilal Farooq
22
24
0
18 Jan 2019
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,266
0
09 Jun 2012
1