Bayesian Scientific Computing

AvDaniela Calvetti,Erkki Somersalo

Inbunden, Engelska, 2023

Del 215 i serien Applied Mathematical Sciences

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Beskrivning

The once esoteric idea of embedding scientific computing into a probabilistic framework, mostly along the lines of the Bayesian paradigm, has recently enjoyed wide popularity and found its way into numerous applications.

Produktinformation

Utgivningsdatum:2023-03-10
Mått:155 x 235 x 22 mm
Vikt:623 g
Format:Inbunden
Språk:Engelska
Serie:Applied Mathematical Sciences
Antal sidor:286
Förlag:Springer International Publishing AG
ISBN:9783031238239

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Recensioner i media

“The book is presented in a logical order, with good writing style. One of the notable features is that the topics are well illustrated with graphs and figures.” (John Masson Noble, Mathematical Reviews, September, 2024)

Innehållsförteckning

Inverse problems and subjective computing.- Linear algebra.- Continuous and discrete multivariate distributions.- Introduction to sampling.- The praise of ignorance: randomness as lack of certainty.- Enter subject: Construction of priors.- Posterior densities, ill-conditioning, and classical regularization.- Conditional Gaussian densities.- Iterative linear solvers and priorconditioners.- Hierarchical models and Bayesian sparsity.- Sampling: the real thing.- Dynamic methods and learning from the past.- Bayesian filtering and Gaussian densities.-