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On a generalization of the preconditioned Crank-Nicolson Metropolis
  algorithm
v1v2 (latest)

On a generalization of the preconditioned Crank-Nicolson Metropolis algorithm

14 April 2015
Daniel Rudolf
Björn Sprungk
ArXiv (abs)PDFHTML

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

25 / 25 papers shown
Title
Reversibility of elliptical slice sampling revisited
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
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
Robust random walk-like Metropolis-Hastings algorithms for concentrating posteriors
Daniel Rudolf
Björn Sprungk
58
6
0
24 Feb 2022
Dimension-independent Markov chain Monte Carlo on the sphere
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
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
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
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
Ensemble sampler for infinite-dimensional inverse problems
Jeremie Coullon
R. Webber
112
10
0
28 Oct 2020
MCMC Algorithms for Posteriors on Matrix Spaces
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
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
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
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
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
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
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
102
66
0
13 Jan 2019
Perturbation Bounds for Monte Carlo within Metropolis via Restricted
  Approximations
Perturbation Bounds for Monte Carlo within Metropolis via Restricted Approximations
F. Medina-Aguayo
Daniel Rudolf
Nikolaus Schweizer
45
25
0
25 Sep 2018
Adaptive Dimension Reduction to Accelerate Infinite-Dimensional
  Geometric Markov Chain Monte Carlo
Adaptive Dimension Reduction to Accelerate Infinite-Dimensional Geometric Markov Chain Monte Carlo
Shiwei Lan
84
10
0
15 Jul 2018
Markov Chain Importance Sampling -- a highly efficient estimator for
  MCMC
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
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
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
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
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
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
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
Geometric ergodicity of the Random Walk Metropolis with position-dependent proposal covariance
Samuel Livingstone
183
11
0
21 Jul 2015
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