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Bayesian Scientific Computing (Hardcover, 1st ed. 2023) Loot Price: R3,182
Discovery Miles 31 820
Bayesian Scientific Computing (Hardcover, 1st ed. 2023): Daniela Calvetti, Erkki Somersalo

Bayesian Scientific Computing (Hardcover, 1st ed. 2023)

Daniela Calvetti, Erkki Somersalo

Series: Applied Mathematical Sciences, 215

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Loot Price R3,182 Discovery Miles 31 820 | Repayment Terms: R298 pm x 12*

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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. This book provides an insider's view of how to combine two mature fields, scientific computing and Bayesian inference, into a powerful language leveraging the capabilities of both components for computational efficiency, high resolution power and uncertainty quantification ability. The impact of Bayesian scientific computing has been particularly significant in the area of computational inverse problems where the data are often scarce or of low quality, but some characteristics of the unknown solution may be available a priori. The ability to combine the flexibility of the Bayesian probabilistic framework with efficient numerical methods has contributed to the popularity of Bayesian inversion, with the prior distribution being the counterpart of classical regularization. However, the interplay between Bayesian inference and numerical analysis is much richer than providing an alternative way to regularize inverse problems, as demonstrated by the discussion of time dependent problems, iterative methods, and sparsity promoting priors in this book. The quantification of uncertainty in computed solutions and model predictions is another area where Bayesian scientific computing plays a critical role. This book demonstrates that Bayesian inference and scientific computing have much more in common than what one may expect, and gradually builds a natural interface between these two areas.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Applied Mathematical Sciences, 215
Release date: March 2023
First published: 2023
Authors: Daniela Calvetti • Erkki Somersalo
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 282
Edition: 1st ed. 2023
ISBN-13: 978-3-03-123823-9
Categories: Books > Science & Mathematics > Mathematics > Numerical analysis
Books > Computing & IT > General theory of computing > Mathematical theory of computation
Books > Science & Mathematics > Mathematics > Algebra > General
Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
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LSN: 3-03-123823-0
Barcode: 9783031238239

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