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A Comparison of Methods for Computing Autocorrelation Time

A Comparison of Methods for Computing Autocorrelation Time

31 October 2010
Madeleine B. Thompson
ArXiv (abs)PDFHTML

Papers citing "A Comparison of Methods for Computing Autocorrelation Time"

15 / 15 papers shown
Emergent interactions lead to collective frustration in robotic matter
Emergent interactions lead to collective frustration in robotic matter
Onurcan Bektas
Adolfo Alsina
Steffen Rulands
189
1
0
29 Jul 2025
Split Hamiltonian Monte Carlo revisited
Split Hamiltonian Monte Carlo revisitedStatistics and computing (Stat. Comput.), 2022
F. Casas
J. Sanz-Serna
Luke Shaw
249
9
0
15 Jul 2022
ParaDRAM: A Cross-Language Toolbox for Parallel High-Performance
  Delayed-Rejection Adaptive Metropolis Markov Chain Monte Carlo Simulations
ParaDRAM: A Cross-Language Toolbox for Parallel High-Performance Delayed-Rejection Adaptive Metropolis Markov Chain Monte Carlo Simulations
A. Shahmoradi
F. Bagheri
197
10
0
21 Aug 2020
Learning interaction kernels in stochastic systems of interacting
  particles from multiple trajectories
Learning interaction kernels in stochastic systems of interacting particles from multiple trajectoriesFoundations of Computational Mathematics (FoCM), 2020
Fei Lu
Mauro Maggioni
Sui Tang
350
57
0
30 Jul 2020
Involutive MCMC: a Unifying Framework
Involutive MCMC: a Unifying Framework
Kirill Neklyudov
Max Welling
Evgenii Egorov
Dmitry Vetrov
264
40
0
30 Jun 2020
Beyond Application End-Point Results: Quantifying Statistical Robustness
  of MCMC Accelerators
Beyond Application End-Point Results: Quantifying Statistical Robustness of MCMC Accelerators
Xinming Zhang
Ramin Bashizade
Yicheng Wang
Cheng Lyu
S. Mukherjee
A. Lebeck
303
5
0
05 Mar 2020
Neural Density Estimation and Likelihood-free Inference
Neural Density Estimation and Likelihood-free Inference
George Papamakarios
BDLDRL
330
59
0
29 Oct 2019
An n-dimensional Rosenbrock Distribution for MCMC Testing
An n-dimensional Rosenbrock Distribution for MCMC Testing
Filippo Pagani
Martin Wiegand
S. Nadarajah
308
25
0
22 Mar 2019
Fast $ε$-free Inference of Simulation Models with Bayesian
  Conditional Density Estimation
Fast εεε-free Inference of Simulation Models with Bayesian Conditional Density Estimation
George Papamakarios
Iain Murray
TPM
515
170
0
20 May 2016
Automated Parameter Blocking for Efficient Markov-Chain Monte Carlo
  Sampling
Automated Parameter Blocking for Efficient Markov-Chain Monte Carlo Sampling
Daniel Turek
P. de Valpine
C. Paciorek
Clifford Anderson-Bergman
305
30
0
19 Mar 2015
Tempering by Subsampling
Tempering by Subsampling
Jan-Willem van de Meent
Brooks Paige
Frank Wood
TPM
257
9
0
28 Jan 2014
Fast Markov chain Monte Carlo sampling for sparse Bayesian inference in
  high-dimensional inverse problems using L1-type priors
Fast Markov chain Monte Carlo sampling for sparse Bayesian inference in high-dimensional inverse problems using L1-type priors
F. Lucka
384
31
0
01 Jun 2012
Split HMC for Gaussian Process Models
Shiwei Lan
Babak Shahbaba
305
2
0
19 Jan 2012
Split Hamiltonian Monte Carlo
Split Hamiltonian Monte CarloStatistics and computing (Stat. Comput.), 2011
Babak Shahbaba
Shiwei Lan
W. Johnson
Radford M. Neal
512
93
0
29 Jun 2011
Graphical Comparison of MCMC Performance
Graphical Comparison of MCMC Performance
Madeleine B. Thompson
205
6
0
19 Nov 2010
1
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