Scalable optimization-based sampling on function space

Scalable optimization-based sampling on function space

3 March 2019

Johnathan M. Bardsley

Youssef Marzouk

Zheng Wang

Papers citing "Scalable optimization-based sampling on function space"

18 / 18 papers shown

Title
Dimension-Robust MCMC in Bayesian Inverse Problems Victor Chen Matthew M. Dunlop O. Papaspiliopoulos Andrew M. Stuart 52 36 0 09 Mar 2018
Parallel local approximation MCMC for expensive models Patrick R. Conrad Andrew D. Davis Youssef Marzouk Natesh Pillai Aaron Smith 42 35 0 10 Jul 2016
Bayesian inverse problems with $l_1$ priors: a Randomize-then-Optimize approach Zheng Wang Johnathan M. Bardsley A. Solonen Tiangang Cui Youssef M. Marzouk 37 38 0 07 Jul 2016
Geometric MCMC for Infinite-Dimensional Inverse Problems A. Beskos Mark Girolami Shiwei Lan P. Farrell Andrew M. Stuart 48 143 0 20 Jun 2016
A randomized maximum a posterior method for posterior sampling of high dimensional nonlinear Bayesian inverse problems Kainan Wang T. Bui-Thanh Omar Ghattas 38 46 0 11 Feb 2016
Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction Tiangang Cui Youssef M. Marzouk Karen E. Willcox 60 62 0 20 Oct 2015
Metropolized Randomized Maximum Likelihood for sampling from multimodal distributions D. Oliver 27 30 0 30 Jul 2015
On a generalization of the preconditioned Crank-Nicolson Metropolis algorithm Daniel Rudolf Björn Sprungk 41 67 0 14 Apr 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 49 200 0 13 Nov 2014
Optimal low-rank approximations of Bayesian linear inverse problems Alessio Spantini A. Solonen Tiangang Cui James Martin L. Tenorio Youssef Marzouk 73 130 0 13 Jul 2014
Likelihood-informed dimension reduction for nonlinear inverse problems Tiangang Cui James Martin Youssef M. Marzouk A. Solonen Alessio Spantini 67 159 0 19 Mar 2014
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
A computational framework for infinite-dimensional Bayesian inverse problems. Part I: The linearized case, with application to global seismic inversion T. Bui-Thanh Omar Ghattas James Martin G. Stadler 71 392 0 06 Aug 2013
Complexity Analysis of Accelerated MCMC Methods for Bayesian Inversion V. H. Hoang Christoph Schwab Andrew M. Stuart 81 112 0 10 Jul 2012
MCMC using Hamiltonian dynamics Radford M. Neal 290 3,276 0 09 Jun 2012
MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster S. Cotter Gareth O. Roberts Andrew M. Stuart D. White 97 480 0 03 Feb 2012
Diffusion limits of the random walk Metropolis algorithm in high dimensions Jonathan C. Mattingly Natesh S. Pillai Andrew M. Stuart 99 114 0 22 Mar 2010