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Merging MCMC Subposteriors through Gaussian-Process Approximations

Merging MCMC Subposteriors through Gaussian-Process Approximations

27 May 2016
Christopher Nemeth
Chris Sherlock
ArXivPDFHTML

Papers citing "Merging MCMC Subposteriors through Gaussian-Process Approximations"

8 / 8 papers shown
Title
Embarrassingly Parallel GFlowNets
Embarrassingly Parallel GFlowNets
Tiago da Silva
Luiz Max Carvalho
Amauri Souza
Samuel Kaski
Diego Mesquita
42
1
0
05 Jun 2024
Machine Learning and the Future of Bayesian Computation
Machine Learning and the Future of Bayesian Computation
Steven Winter
Trevor Campbell
Lizhen Lin
Sanvesh Srivastava
David B. Dunson
TPM
33
4
0
21 Apr 2023
Federated Averaging Langevin Dynamics: Toward a unified theory and new
  algorithms
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms
Vincent Plassier
Alain Durmus
Eric Moulines
FedML
14
6
0
31 Oct 2022
Federated Stochastic Gradient Langevin Dynamics
Federated Stochastic Gradient Langevin Dynamics
Khaoula El Mekkaoui
Diego Mesquita
P. Blomstedt
Samuel Kaski
FedML
16
24
0
23 Apr 2020
Stochastic gradient Markov chain Monte Carlo
Stochastic gradient Markov chain Monte Carlo
Christopher Nemeth
Paul Fearnhead
BDL
16
135
0
16 Jul 2019
Embarrassingly parallel MCMC using deep invertible transformations
Embarrassingly parallel MCMC using deep invertible transformations
Diego Mesquita
P. Blomstedt
Samuel Kaski
9
18
0
11 Mar 2019
Hamiltonian Monte Carlo with Energy Conserving Subsampling
Hamiltonian Monte Carlo with Energy Conserving Subsampling
Khue-Dung Dang
M. Quiroz
Robert Kohn
Minh-Ngoc Tran
M. Villani
25
62
0
02 Aug 2017
Control Variates for Stochastic Gradient MCMC
Control Variates for Stochastic Gradient MCMC
Jack Baker
Paul Fearnhead
E. Fox
Christopher Nemeth
BDL
25
101
0
16 Jun 2017
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