A Bayesian level set method for geometric inverse problems

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A Bayesian level set method for geometric inverse problems

We introduce a level set based approach to Bayesian geometric inverse problems. In these problems the interface between different domains is the key unknown, and is realized as the level set of a function. This function itself becomes the object of the inference. Whilst the level set methodology has...

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Bibliographic Details
Main Authors:	Iglesias, Marco, Lu, Yulong, Stuart, Andrew
Format:	Article
Published:	European Mathematical Society 2016
Subjects:	Inverse problems Bayesian level set method Markov chain Monte Carlo (MCMC)
Online Access:	https://eprints.nottingham.ac.uk/40925/

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