Local estimators and Bayesian inverse problems with non-unique solutions

Jiguang Sun

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arXiv · 2105.09141

Local estimators and Bayesian inverse problems with non-unique solutions

Jiguang Sun

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Abstract

The Bayesian approach is effective for inverse problems. The posterior density distribution provides useful information of the unknowns. However, for problems with non-unique solutions, the classical estimators such as the maximum a posterior (MAP) and conditional mean (CM) are not enough. We introduce two new estimators, the local maximum a posterior (LMAP) and local conditional mean (LCM). Their applications are demonstrated by three inverse problems: an inverse spectral problem, an inverse source problem, and an inverse medium problem.

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Jiguang Sun. 2021-05-19. Local estimators and Bayesian inverse problems with non-unique solutions. https://arxiv.org/abs/2105.09141

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