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On a generalization of the preconditioned Crank-Nicolson Metropolis algorithm

14 April 2015

Papers citing "On a generalization of the preconditioned Crank-Nicolson Metropolis algorithm"

25 / 25 papers shown

Title
Reversibility of elliptical slice sampling revisited Mareike Hasenpflug Viacheslav Natarovskii Daniel Rudolf 95 5 0 06 Jan 2023
Generative models and Bayesian inversion using Laplace approximation M. Marschall G. Wübbeler F. Schmähling Clemens Elster 59 1 0 15 Mar 2022
Robust random walk-like Metropolis-Hastings algorithms for concentrating posteriors Daniel Rudolf Björn Sprungk 56 6 0 24 Feb 2022
Dimension-independent Markov chain Monte Carlo on the sphere H. Lie Daniel Rudolf Björn Sprungk T. Sullivan 80 6 0 22 Dec 2021
hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty Ki-tae Kim Umberto Villa M. Parno Youssef Marzouk Omar Ghattas N. Petra 82 19 0 01 Dec 2021
Geometric convergence of elliptical slice sampling Viacheslav Natarovskii Daniel Rudolf Björn Sprungk 68 12 0 07 May 2021
A unified performance analysis of likelihood-informed subspace methods Tiangang Cui X. Tong 64 26 0 07 Jan 2021
Ensemble sampler for infinite-dimensional inverse problems Jeremie Coullon R. Webber 112 10 0 28 Oct 2020
MCMC Algorithms for Posteriors on Matrix Spaces A. Beskos K. Kamatani 141 1 0 07 Aug 2020
Non-Stationary Multi-layered Gaussian Priors for Bayesian Inversion M. Emzir Sari Lasanen Z. Purisha L. Roininen Simo Särkkä 78 9 0 28 Jun 2020
Data-Driven Forward Discretizations for Bayesian Inversion Daniele Bigoni Yuming Chen Nicolas García Trillos Youssef Marzouk D. Sanz-Alonso AI4CE 86 11 0 18 Mar 2020
Optimization-Based MCMC Methods for Nonlinear Hierarchical Statistical Inverse Problems Johnathan M. Bardsley Tiangang Cui 41 1 0 15 Feb 2020
MALA-within-Gibbs samplers for high-dimensional distributions with sparse conditional structure X. Tong M. Morzfeld Y. M. Marzouk 73 28 0 26 Aug 2019
Scalable optimization-based sampling on function space Johnathan M. Bardsley Tiangang Cui Youssef Marzouk Zheng Wang 80 18 0 03 Mar 2019
On the Convergence of the Laplace Approximation and Noise-Level-Robustness of Laplace-based Monte Carlo Methods for Bayesian Inverse Problems C. Schillings Björn Sprungk Philipp Wacker 97 66 0 13 Jan 2019
Perturbation Bounds for Monte Carlo within Metropolis via Restricted Approximations F. Medina-Aguayo Daniel Rudolf Nikolaus Schweizer 43 25 0 25 Sep 2018
Adaptive Dimension Reduction to Accelerate Infinite-Dimensional Geometric Markov Chain Monte Carlo Shiwei Lan 81 10 0 15 Jul 2018
Markov Chain Importance Sampling -- a highly efficient estimator for MCMC Ingmar Schuster I. Klebanov 114 24 0 18 May 2018
On the Consistency of Graph-based Bayesian Learning and the Scalability of Sampling Algorithms Nicolas García Trillos Zachary T. Kaplan Thabo Samakhoana D. Sanz-Alonso 68 19 0 20 Oct 2017
Complexity Results for MCMC derived from Quantitative Bounds Jun Yang Jeffrey S. Rosenthal 84 24 0 02 Aug 2017
Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals A. Beskos Ajay Jasra K. Law Youssef Marzouk Yan Zhou 80 42 0 15 Mar 2017
Geometric MCMC for Infinite-Dimensional Inverse Problems A. Beskos Mark Girolami Shiwei Lan P. Farrell Andrew M. Stuart 92 144 0 20 Jun 2016
Ergodicity of Markov chain Monte Carlo with reversible proposal K. Kamatani 45 11 0 09 Feb 2016
On an adaptive preconditioned Crank-Nicolson MCMC algorithm for infinite dimensional Bayesian inferences Zixi Hu Z. Yao Jinglai Li 60 20 0 18 Nov 2015
Geometric ergodicity of the Random Walk Metropolis with position-dependent proposal covariance Samuel Livingstone 183 11 0 21 Jul 2015