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Parallel local approximation MCMC for expensive models

Parallel local approximation MCMC for expensive models

10 July 2016
Patrick R. Conrad
Andrew D. Davis
Youssef Marzouk
Natesh Pillai
Aaron Smith
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Papers citing "Parallel local approximation MCMC for expensive models"

6 / 6 papers shown
Title
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC
F. Llorente
Luca Martino
Jesse Read
D. Delgado
OffRL
140
13
0
03 Jan 2025
Scalable posterior approximations for large-scale Bayesian inverse
  problems via likelihood-informed parameter and state reduction
Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction
Tiangang Cui
Youssef M. Marzouk
Karen E. Willcox
63
62
0
20 Oct 2015
Accelerating Asymptotically Exact MCMC for Computationally Intensive
  Models via Local Approximations
Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations
Patrick R. Conrad
Youssef M. Marzouk
Natesh S. Pillai
Aaron Smith
84
116
0
07 Feb 2014
Adaptive construction of surrogates for the Bayesian solution of inverse
  problems
Adaptive construction of surrogates for the Bayesian solution of inverse problems
Jinglai Li
Youssef M. Marzouk
62
118
0
21 Sep 2013
A computational framework for infinite-dimensional Bayesian inverse
  problems: Part II. Stochastic Newton MCMC with application to ice sheet flow
  inverse problems
A computational framework for infinite-dimensional Bayesian inverse problems: Part II. Stochastic Newton MCMC with application to ice sheet flow inverse problems
N. Petra
James Martin
G. Stadler
Omar Ghattas
68
231
0
28 Aug 2013
Uncertainty quantification and weak approximation of an elliptic inverse
  problem
Uncertainty quantification and weak approximation of an elliptic inverse problem
Masoumeh Dashti
Andrew M. Stuart
62
102
0
01 Feb 2011
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