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dc.contributor.editorTang, Niansheng
dc.date.accessioned2023-02-15T14:51:28Z
dc.date.available2023-02-15T14:51:28Z
dc.date.issued2022
dc.identifierONIX_20230215_9781803560458_272
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/97233
dc.description.abstractWith growing interest in data mining and its merits, including the incorporation of historical or experiential information into statistical analysis, Bayesian inference has become an important tool for analyzing complicated data and solving inverse problems in various fields such as artificial intelligence. This book introduces recent developments in Bayesian inference, and covers a variety of topics including robust Bayesian estimation, solving inverse problems via Bayesian theories, hierarchical Bayesian inference, and its applications for scattering experiments. We hope that this book will stimulate more extensive research on Bayesian fronts to include theories, methods, computational algorithms and applications in various fields such as data science, AI, machine learning, and causality analysis.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYM Computer modelling and simulationen_US
dc.subject.otherComputer science
dc.titleBayesian Inference
dc.title.alternativeRecent Advantages
dc.typebook
oapen.identifier.doi10.5772/intechopen.97942
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6
oapen.relation.isbn9781803560458
oapen.relation.isbn9781803560441
oapen.relation.isbn9781803560465
oapen.imprintIntechOpen
oapen.pages126


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