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Exploiting Multi-Core Architectures for Reduced-Variance Estimation with
  Intractable Likelihoods
v1v2 (latest)

Exploiting Multi-Core Architectures for Reduced-Variance Estimation with Intractable Likelihoods

20 August 2014
Nial Friel
Antonietta Mira
Chris J. Oates
ArXiv (abs)PDFHTML

Papers citing "Exploiting Multi-Core Architectures for Reduced-Variance Estimation with Intractable Likelihoods"

13 / 13 papers shown
Title
Meta-learning Control Variates: Variance Reduction with Limited Data
Meta-learning Control Variates: Variance Reduction with Limited Data
Z. Sun
Chris J. Oates
F. Briol
BDL
94
9
0
08 Mar 2023
Variance reduction for dependent sequences with applications to
  Stochastic Gradient MCMC
Variance reduction for dependent sequences with applications to Stochastic Gradient MCMC
Denis Belomestny
L. Iosipoi
Eric Moulines
A. Naumov
S. Samsonov
66
6
0
16 Aug 2020
Scalable Control Variates for Monte Carlo Methods via Stochastic
  Optimization
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization
Shijing Si
Chris J. Oates
Andrew B. Duncan
Lawrence Carin
F. Briol
BDL
56
21
0
12 Jun 2020
Semi-Exact Control Functionals From Sard's Method
Semi-Exact Control Functionals From Sard's Method
Leah F. South
Toni Karvonen
Christopher Nemeth
Mark Girolami
Chris J. Oates
78
17
0
31 Jan 2020
Bayesian Model Selection for High-Dimensional Ising Models, With
  Applications to Educational Data
Bayesian Model Selection for High-Dimensional Ising Models, With Applications to Educational Data
Jaewoo Park
Ick Hoon Jin
M. Schweinberger
44
7
0
17 Nov 2019
Particle Methods for Stochastic Differential Equation Mixed Effects
  Models
Particle Methods for Stochastic Differential Equation Mixed Effects Models
Imke Botha
Robert Kohn
Christopher C. Drovandi
51
21
0
25 Jul 2019
A Kernel Stein Test for Comparing Latent Variable Models
A Kernel Stein Test for Comparing Latent Variable Models
Heishiro Kanagawa
Wittawat Jitkrittum
Lester W. Mackey
Kenji Fukumizu
Arthur Gretton
80
13
0
01 Jul 2019
Regularized Zero-Variance Control Variates
Regularized Zero-Variance Control Variates
Leah F. South
Chris J. Oates
Antonietta Mira
Christopher C. Drovandi
BDL
104
19
0
13 Nov 2018
Efficient MCMC for Gibbs Random Fields using pre-computation
Efficient MCMC for Gibbs Random Fields using pre-computation
A. Boland
Nial Friel
Florian Maire
90
19
0
11 Oct 2017
Noisy Hamiltonian Monte Carlo for doubly-intractable distributions
Noisy Hamiltonian Monte Carlo for doubly-intractable distributions
Julien Stoehr
Alan Benson
Nial Friel
53
11
0
30 Jun 2017
Control Variates for Stochastic Gradient MCMC
Control Variates for Stochastic Gradient MCMC
Jack Baker
Paul Fearnhead
E. Fox
Christopher Nemeth
BDL
91
101
0
16 Jun 2017
Optimal approximating Markov chains for Bayesian inference
Optimal approximating Markov chains for Bayesian inference
J. Johndrow
Jonathan C. Mattingly
Sayan Mukherjee
David B. Dunson
98
31
0
13 Aug 2015
Ergodicity of Approximate MCMC Chains with Applications to Large Data
  Sets
Ergodicity of Approximate MCMC Chains with Applications to Large Data Sets
Natesh S. Pillai
Aaron Smith
96
59
0
01 May 2014
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