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On the Bernstein-Von Mises Theorem for High Dimensional Nonlinear
  Bayesian Inverse Problems

On the Bernstein-Von Mises Theorem for High Dimensional Nonlinear Bayesian Inverse Problems

1 June 2017
Yulong Lu
ArXivPDFHTML

Papers citing "On the Bernstein-Von Mises Theorem for High Dimensional Nonlinear Bayesian Inverse Problems"

5 / 5 papers shown
Title
Tight Bounds on the Laplace Approximation Accuracy in High Dimensions
A. Katsevich
27
5
0
28 May 2023
Dimension free non-asymptotic bounds on the accuracy of high dimensional
  Laplace approximation
Dimension free non-asymptotic bounds on the accuracy of high dimensional Laplace approximation
V. Spokoiny
33
22
0
23 Apr 2022
Non-asymptotic error estimates for the Laplace approximation in Bayesian
  inverse problems
Non-asymptotic error estimates for the Laplace approximation in Bayesian inverse problems
T. Helin
Remo Kretschmann
16
17
0
11 Dec 2020
Bayesian Generative Models for Knowledge Transfer in MRI Semantic
  Segmentation Problems
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems
Anna Kuzina
Evgenii Egorov
Evgeny Burnaev
MedIm
29
19
0
15 Aug 2019
A Bernstein-Von Mises Theorem for discrete probability distributions
A Bernstein-Von Mises Theorem for discrete probability distributions
S. Boucheron
Elisabeth Gassiat
113
49
0
14 Jul 2008
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