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Bernstein-von Mises theorems and uncertainty quantification for linear inverse problems
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Bernstein-von Mises theorems and uncertainty quantification for linear inverse problems

M. Giordano
Hanne Kekkonen
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Papers citing "Bernstein-von Mises theorems and uncertainty quantification for linear inverse problems"

10 / 10 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
49
0
0
29 Feb 2024
Are minimizers of the Onsager-Machlup functional strong posterior modes?
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
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
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
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
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
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
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
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
Bernstein -- von Mises theorems for statistical inverse problems II: Compound Poisson processes
Richard Nickl
Jakob Sohl
69
36
0
22 Sep 2017