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1811.04058
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Bernstein-von Mises theorems and uncertainty quantification for linear inverse problems
9 November 2018
M. Giordano
Hanne Kekkonen
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Papers citing
"Bernstein-von Mises theorems and uncertainty quantification for linear inverse problems"
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Title
A Bayesian approach with Gaussian priors to the inverse problem of source identification in elliptic PDEs
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49
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29 Feb 2024
Are minimizers of the Onsager-Machlup functional strong posterior modes?
Remo Kretschmann
72
1
0
08 Dec 2022
A Bernstein--von-Mises theorem for the Calderón problem with piecewise constant conductivities
Jan Bohr
62
2
0
16 Jun 2022
Dimension free non-asymptotic bounds on the accuracy of high dimensional Laplace approximation
V. Spokoiny
93
22
0
23 Apr 2022
Convergence Rates for Learning Linear Operators from Noisy Data
Maarten V. de Hoop
Nikola B. Kovachki
Nicholas H. Nelsen
Andrew M. Stuart
182
58
0
27 Aug 2021
On some information-theoretic aspects of non-linear statistical inverse problems
Richard Nickl
G. Paternain
79
9
0
20 Jul 2021
Non-asymptotic error estimates for the Laplace approximation in Bayesian inverse problems
T. Helin
Remo Kretschmann
61
18
0
11 Dec 2020
Statistical guarantees for Bayesian uncertainty quantification in non-linear inverse problems with Gaussian process priors
F. Monard
Richard Nickl
G. Paternain
61
36
0
31 Jul 2020
Nonparametric statistical inference for drift vector fields of multi-dimensional diffusions
Richard Nickl
Kolyan Ray
81
52
0
03 Oct 2018
Bernstein -- von Mises theorems for statistical inverse problems II: Compound Poisson processes
Richard Nickl
Jakob Sohl
69
36
0
22 Sep 2017
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