Efficient Marginalization-based MCMC Methods for Hierarchical Bayesian Inverse Problems

2 November 2018

Papers citing "Efficient Marginalization-based MCMC Methods for Hierarchical Bayesian Inverse Problems"

9 / 9 papers shown

Title
Fast sampling in a linear-Gaussian inverse problem C. Fox R. Norton 41 35 0 06 Jul 2015
Transport map accelerated Markov chain Monte Carlo M. Parno Youssef Marzouk OT 80 161 0 17 Dec 2014
Dimension-independent likelihood-informed MCMC Tiangang Cui K. Law Youssef M. Marzouk 49 198 0 13 Nov 2014
Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet T. Isaac N. Petra G. Stadler Omar Ghattas PINN 54 153 0 05 Oct 2014
Optimal low-rank approximations of Bayesian linear inverse problems Alessio Spantini A. Solonen Tiangang Cui James Martin L. Tenorio Youssef Marzouk 68 130 0 13 Jul 2014
Analysis of the Gibbs sampler for hierarchical inverse problems S. Agapiou Johnathan M. Bardsley O. Papaspiliopoulos Andrew M. Stuart 64 60 0 05 Nov 2013
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
MCMC using Hamiltonian dynamics Radford M. Neal 288 3,276 0 09 Jun 2012
The pseudo-marginal approach for efficient Monte Carlo computations Christophe Andrieu Gareth O. Roberts 156 894 0 31 Mar 2009