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Orthogonal parallel MCMC methods for sampling and optimization

Orthogonal parallel MCMC methods for sampling and optimization

30 July 2015
Luca Martino
Victor Elvira
D. Luengo
J. Corander
F. Louzada
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Papers citing "Orthogonal parallel MCMC methods for sampling and optimization"

15 / 15 papers shown
Title
Improving Population Monte Carlo: Alternative Weighting and Resampling
  Schemes
Improving Population Monte Carlo: Alternative Weighting and Resampling Schemes
Victor Elvira
Luca Martino
D. Luengo
M. Bugallo
61
85
0
10 Jul 2016
Parallel Metropolis chains with cooperative adaptation
Parallel Metropolis chains with cooperative adaptation
Luca Martino
Victor Elvira
D. Luengo
F. Louzada
35
4
0
26 Sep 2015
Issues in the Multiple Try Metropolis mixing
Issues in the Multiple Try Metropolis mixing
Luca Martino
F. Louzada
20
23
0
18 Aug 2015
Parallelizing MCMC with Random Partition Trees
Parallelizing MCMC with Random Partition Trees
Xiangyu Wang
Fangjian Guo
Katherine A. Heller
David B. Dunson
86
76
0
10 Jun 2015
Efficient Multiple Importance Sampling Estimators
Efficient Multiple Importance Sampling Estimators
Victor Elvira
Luca Martino
D. Luengo
M. Bugallo
64
75
0
20 May 2015
On Markov chain Monte Carlo methods for tall data
On Markov chain Monte Carlo methods for tall data
Rémi Bardenet
Arnaud Doucet
Chris Holmes
71
279
0
11 May 2015
Parallelizing MCMC via Weierstrass Sampler
Parallelizing MCMC via Weierstrass Sampler
Xiangyu Wang
David B. Dunson
91
138
0
17 Dec 2013
Asymptotically Exact, Embarrassingly Parallel MCMC
Asymptotically Exact, Embarrassingly Parallel MCMC
Willie Neiswanger
Chong-Jun Wang
Eric Xing
FedML
83
330
0
19 Nov 2013
Fully Adaptive Gaussian Mixture Metropolis-Hastings Algorithm
Fully Adaptive Gaussian Mixture Metropolis-Hastings Algorithm
D. Luengo
Luca Martino
93
35
0
01 Dec 2012
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
290
3,281
0
09 Jun 2012
Improved Adaptive Rejection Metropolis Sampling Algorithms
Improved Adaptive Rejection Metropolis Sampling Algorithms
Luca Martino
Jesse Read
D. Luengo
57
86
0
24 May 2012
On the flexibility of the design of Multiple Try Metropolis schemes
On the flexibility of the design of Multiple Try Metropolis schemes
Luca Martino
Jesse Read
84
61
0
03 Jan 2012
A multi-point Metropolis scheme with generic weight functions
A multi-point Metropolis scheme with generic weight functions
Luca Martino
V. D. Olmo
Jesse Read
65
34
0
17 Dec 2011
MCMC Using Ensembles of States for Problems with Fast and Slow Variables
  such as Gaussian Process Regression
MCMC Using Ensembles of States for Problems with Fast and Slow Variables such as Gaussian Process Regression
Radford M. Neal
73
38
0
02 Jan 2011
Using parallel computation to improve Independent Metropolis--Hastings
  based estimation
Using parallel computation to improve Independent Metropolis--Hastings based estimation
Pierre E. Jacob
Christian P. Robert
Murray H. Smith
93
62
0
08 Oct 2010
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