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

9 November 2018

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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 Matteo Giordano 49 0 0 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