Well-posedness of Bayesian inverse problems for hyperbolic conservation laws


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Date

2021-07

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Report

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Abstract

We study the well-posedness of the Bayesian inverse problem for scalar hyperbolic conservation laws where the statistical information about inputs such as the initial datum and (possibly discontinuous) flux function are inferred from noisy measurements. In particular, the Lipschitz continuity of the measurement to posterior map as well as the stability of the posterior to approximations, are established with respect to the Wasserstein distance. Numerical experiments are presented to illustrate the derived estimates.

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published

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2021-24

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Publisher

Seminar for Applied Mathematics, ETH Zurich

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Subject

Inverse problem; Bayesian; Wasserstein distance; Conservation laws

Organisational unit

03851 - Mishra, Siddhartha / Mishra, Siddhartha check_circle

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