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A gradient-free subspace-adjusting ensemble sampler for
  infinite-dimensional Bayesian inverse problems

A gradient-free subspace-adjusting ensemble sampler for infinite-dimensional Bayesian inverse problems

22 February 2022
Matthew M. Dunlop
G. Stadler
    BDL
ArXivPDFHTML

Papers citing "A gradient-free subspace-adjusting ensemble sampler for infinite-dimensional Bayesian inverse problems"

6 / 6 papers shown
Title
New affine invariant ensemble samplers and their dimensional scaling
New affine invariant ensemble samplers and their dimensional scaling
Yifan Chen
42
0
0
05 May 2025
Ensemble-Based Annealed Importance Sampling
Ensemble-Based Annealed Importance Sampling
Haoxuan Chen
Lexing Ying
41
2
0
28 Jan 2024
Metropolis-adjusted interacting particle sampling
Metropolis-adjusted interacting particle sampling
Bjorn Sprungk
Simon Weissmann
Jakob Zech
31
7
0
21 Dec 2023
Sampling via Gradient Flows in the Space of Probability Measures
Sampling via Gradient Flows in the Space of Probability Measures
Yifan Chen
Daniel Zhengyu Huang
Jiaoyang Huang
Sebastian Reich
Andrew M. Stuart
44
13
0
05 Oct 2023
Object based Bayesian full-waveform inversion for shear elastography
Object based Bayesian full-waveform inversion for shear elastography
A. Carpio
E. Cebrián
Andrea Gutierrez
28
1
0
11 May 2023
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations
  and Affine Invariance
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance
Yifan Chen
Daniel Zhengyu Huang
Jiaoyang Huang
Sebastian Reich
Andrew M. Stuart
39
17
0
21 Feb 2023
1