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An Efficient Minibatch Acceptance Test for Metropolis-Hastings
v1v2v3 (latest)

An Efficient Minibatch Acceptance Test for Metropolis-Hastings

19 October 2016
Daniel Seita
Xinlei Pan
Haoyu Chen
John F. Canny
ArXiv (abs)PDFHTML

Papers citing "An Efficient Minibatch Acceptance Test for Metropolis-Hastings"

14 / 14 papers shown
Title
Textual Bayes: Quantifying Uncertainty in LLM-Based Systems
Textual Bayes: Quantifying Uncertainty in LLM-Based Systems
Brendan Leigh Ross
Noël Vouitsis
Atiyeh Ashari Ghomi
Rasa Hosseinzadeh
Ji Xin
...
Yi Sui
Shiyi Hou
Kin Kwan Leung
Gabriel Loaiza-Ganem
Jesse C. Cresswell
67
0
0
11 Jun 2025
Bayesian Data Sketching for Varying Coefficient Regression Models
Bayesian Data Sketching for Varying Coefficient Regression Models
Rajarshi Guhaniyogi
Laura Baracaldo
Sudipto Banerjee
31
5
0
30 May 2025
Enhancing Gradient-based Discrete Sampling via Parallel Tempering
Enhancing Gradient-based Discrete Sampling via Parallel Tempering
Luxu Liang
Yuhang Jia
Feng Zhou
152
0
0
26 Feb 2025
Some Examples of Privacy-preserving Publication and Sharing of COVID-19
  Pandemic Data
Some Examples of Privacy-preserving Publication and Sharing of COVID-19 Pandemic Data
Fan Liu
Dong Wang
Tian Yan
53
1
0
18 Jun 2021
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
Wei Deng
Qi Feng
Liyao (Mars) Gao
F. Liang
Guang Lin
BDL
77
47
0
12 Aug 2020
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic
  Gradient MCMC
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC
Ruqi Zhang
A. Feder Cooper
Christopher De Sa
83
18
0
29 Feb 2020
Challenges in Markov chain Monte Carlo for Bayesian neural networks
Challenges in Markov chain Monte Carlo for Bayesian neural networks
Theodore Papamarkou
Jacob D. Hinkle
M. T. Young
D. Womble
BDL
131
51
0
15 Oct 2019
Replica-exchange Nosé-Hoover dynamics for Bayesian learning on large
  datasets
Replica-exchange Nosé-Hoover dynamics for Bayesian learning on large datasets
Rui Luo
Qiang Zhang
Yaodong Yang
Jun Wang
BDL
71
3
0
29 May 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
Ruqi Zhang
Chunyuan Li
Jianyi Zhang
Changyou Chen
A. Wilson
BDL
88
278
0
11 Feb 2019
Differentially Private Markov Chain Monte Carlo
Differentially Private Markov Chain Monte Carlo
Mikko A. Heikkilä
Hibiki Ito
O. Dikmen
Antti Honkela
69
26
0
29 Jan 2019
Metropolis-Hastings view on variational inference and adversarial
  training
Metropolis-Hastings view on variational inference and adversarial training
Kirill Neklyudov
Evgenii Egorov
Pavel Shvechikov
Dmitry Vetrov
GAN
76
13
0
16 Oct 2018
Minibatch Gibbs Sampling on Large Graphical Models
Minibatch Gibbs Sampling on Large Graphical Models
Christopher De Sa
Vincent Chen
W. Wong
71
20
0
15 Jun 2018
Parallel Markov Chain Monte Carlo for Bayesian Hierarchical Models with
  Big Data, in Two Stages
Parallel Markov Chain Monte Carlo for Bayesian Hierarchical Models with Big Data, in Two Stages
Zheng Wei
Erin M. Conlon
63
3
0
16 Dec 2017
Mini-batch Tempered MCMC
Mini-batch Tempered MCMC
Dangna Li
W. Wong
70
6
0
31 Jul 2017
1