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Mini-batch Metropolis-Hastings MCMC with Reversible SGLD Proposal

Mini-batch Metropolis-Hastings MCMC with Reversible SGLD Proposal

8 August 2019
Tung-Yu Wu
Y. X. R. Wang
W. Wong
ArXivPDFHTML

Papers citing "Mini-batch Metropolis-Hastings MCMC with Reversible SGLD Proposal"

5 / 5 papers shown
Title
Minibatch Markov chain Monte Carlo Algorithms for Fitting Gaussian
  Processes
Minibatch Markov chain Monte Carlo Algorithms for Fitting Gaussian Processes
Matthew J. Heaton
Jacob A. Johnson
22
1
0
26 Oct 2023
Masked Bayesian Neural Networks : Theoretical Guarantee and its
  Posterior Inference
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference
Insung Kong
Dongyoon Yang
Jongjin Lee
Ilsang Ohn
Gyuseung Baek
Yongdai Kim
BDL
43
4
0
24 May 2023
Density Regression and Uncertainty Quantification with Bayesian Deep
  Noise Neural Networks
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks
Daiwei Zhang
Tianci Liu
Jian Kang
BDL
UQCV
43
2
0
12 Jun 2022
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis
  of Big Data
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data
J. Bierkens
Paul Fearnhead
Gareth O. Roberts
58
231
0
11 Jul 2016
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
192
3,268
0
09 Jun 2012
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