Solving inverse problems with Bayes' theorem

dc.bibliographicCitation.seriesTitle	Snapshots of Modern Mathematics from Oberwolfach	eng
dc.bibliographicCitation.volume	6/2022
dc.contributor.author	Latz, Jonas
dc.contributor.author	Sprungk, Björn
dc.date.accessioned	2024-10-16T13:55:09Z
dc.date.available	2024-10-16T13:55:09Z
dc.date.issued	2022
dc.description.abstract	The goal of inverse problems is to find an unknown parameter based on noisy data. Such problems appear in a wide range of applications including geophysics, medicine, and chemistry. One method of solving them is known as the Bayesian approach. In this approach, the unknown parameter is modelled as a random variable to reflect its uncertain value. Bayes' theorem is applied to update our knowledge given new information from noisy data.
dc.description.version	publishedVersion
dc.identifier.uri	https://oa.tib.eu/renate/handle/123456789/16852
dc.identifier.uri	https://doi.org/10.34657/15874
dc.language.iso	eng
dc.publisher	Oberwolfach : Mathematisches Forschungsinstitut Oberwolfach gGmbH
dc.relation.doi	https://doi.org/10.14760/SNAP-2022-006-EN
dc.relation.essn	2626-1995
dc.rights.license	CC BY-SA 4.0 Unported
dc.rights.uri	http://creativecommons.org/licenses/by-sa/4.0/
dc.subject.ddc	510
dc.subject.other	Numerics and Scientific Computing
dc.subject.other	Probability Theory and Statistics
dc.title	Solving inverse problems with Bayes' theorem
dc.type	Report
dc.type	Text

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