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Analysis of the Gibbs sampler for hierarchical inverse problems
v1v2v3 (latest)

Analysis of the Gibbs sampler for hierarchical inverse problems

5 November 2013
S. Agapiou
Johnathan M. Bardsley
O. Papaspiliopoulos
Andrew M. Stuart
ArXiv (abs)PDFHTML

Papers citing "Analysis of the Gibbs sampler for hierarchical inverse problems"

19 / 19 papers shown
Title
A Bayesian approach with Gaussian priors to the inverse problem of
  source identification in elliptic PDEs
A Bayesian approach with Gaussian priors to the inverse problem of source identification in elliptic PDEs
Matteo Giordano
43
0
0
29 Feb 2024
Adaptive inference over Besov spaces in the white noise model using
  $p$-exponential priors
Adaptive inference over Besov spaces in the white noise model using ppp-exponential priors
S. Agapiou
Aimilia Savva
117
4
0
13 Sep 2022
A Variational Inference Approach to Inverse Problems with Gamma
  Hyperpriors
A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors
Shivendra Agrawal
Hwanwoo Kim
D. Sanz-Alonso
A. Strang
63
10
0
26 Nov 2021
Convergence Rates for Learning Linear Operators from Noisy Data
Convergence Rates for Learning Linear Operators from Noisy Data
Maarten V. de Hoop
Nikola B. Kovachki
Nicholas H. Nelsen
Andrew M. Stuart
171
58
0
27 Aug 2021
A hybrid Gibbs sampler for edge-preserving tomographic reconstruction
  with uncertain view angles
A hybrid Gibbs sampler for edge-preserving tomographic reconstruction with uncertain view angles
Felipe Uribe
Johnathan M. Bardsley
Yiqiu Dong
P. Hansen
N. A. B. Riis
50
13
0
14 Apr 2021
Consistency analysis of bilevel data-driven learning in inverse problems
Consistency analysis of bilevel data-driven learning in inverse problems
Neil K. Chada
C. Schillings
Xin T. Tong
Simon Weissmann
58
8
0
06 Jul 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
Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations
  and Consistency
Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations and Consistency
Matthew M. Dunlop
T. Helin
Andrew M. Stuart
72
18
0
10 May 2019
Efficient Marginalization-based MCMC Methods for Hierarchical Bayesian
  Inverse Problems
Efficient Marginalization-based MCMC Methods for Hierarchical Bayesian Inverse Problems
A. Saibaba
Johnathan M. Bardsley
D. Brown
A. Alexanderian
36
13
0
02 Nov 2018
Dimension-Robust MCMC in Bayesian Inverse Problems
Dimension-Robust MCMC in Bayesian Inverse Problems
Victor Chen
Matthew M. Dunlop
O. Papaspiliopoulos
Andrew M. Stuart
65
36
0
09 Mar 2018
Sampling strategies for fast updating of Gaussian Markov random fields
Sampling strategies for fast updating of Gaussian Markov random fields
D. Brown
C. McMahan
Stella Watson Self
84
10
0
17 Feb 2017
Tuning of MCMC with Langevin, Hamiltonian, and other stochastic
  autoregressive proposals
Tuning of MCMC with Langevin, Hamiltonian, and other stochastic autoregressive proposals
R. Norton
C. Fox
36
3
0
03 Oct 2016
Low Rank Independence Samplers in Bayesian Inverse Problems
Low Rank Independence Samplers in Bayesian Inverse Problems
D. Brown
A. Saibaba
Sarah Vallélian
78
4
0
22 Sep 2016
Well-posed Bayesian Inverse Problems: Priors with Exponential Tails
Well-posed Bayesian Inverse Problems: Priors with Exponential Tails
Bamdad Hosseini
N. Nigam
66
46
0
09 Apr 2016
Fast Gibbs sampling for high-dimensional Bayesian inversion
Fast Gibbs sampling for high-dimensional Bayesian inversion
F. Lucka
55
16
0
27 Feb 2016
Fast sampling in a linear-Gaussian inverse problem
Fast sampling in a linear-Gaussian inverse problem
C. Fox
R. Norton
68
35
0
06 Jul 2015
Gaussian process methods for one-dimensional diffusions: optimal rates
  and adaptation
Gaussian process methods for one-dimensional diffusions: optimal rates and adaptation
J. van Waaij
Harry Van Zanten
114
37
0
01 Jun 2015
Unbiased Monte Carlo: posterior estimation for
  intractable/infinite-dimensional models
Unbiased Monte Carlo: posterior estimation for intractable/infinite-dimensional models
S. Agapiou
Gareth O. Roberts
Sebastian J. Vollmer
71
13
0
27 Nov 2014
Preconditioning the prior to overcome saturation in Bayesian inverse
  problems
Preconditioning the prior to overcome saturation in Bayesian inverse problems
S. Agapiou
Peter Mathé
58
2
0
23 Sep 2014
1