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Books > Science & Mathematics > Mathematics > Algebra
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Bayesian Scientific Computing (Hardcover, 1st ed. 2023)
Loot Price: R3,722
Discovery Miles 37 220
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Bayesian Scientific Computing (Hardcover, 1st ed. 2023)
Series: Applied Mathematical Sciences, 215
Expected to ship within 10 - 15 working days
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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.
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