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Probabilistic Numerics
- Computation as Machine Learning
Engelsk
Bogcover for Probabilistic Numerics af Hans P. Kersting, Michael A. Osborne, Philipp Hennig, 9781107163447
Specifikationer
Sprog:
Engelsk
Sider:
410
ISBN-13:
9781107163447
Indbinding:
Hardback
Udgave:
ISBN-10:
1107163447
Kategori:
Udg. Dato:
30 jun 2022
Længde:
25mm
Bredde:
259mm
Højde:
211mm
Forlag:
Cambridge University Press
Oplagsdato:
30 jun 2022
Hardback
Format:

Om denne bog
Probabilistic numerical computation formalises the connection between machine learning and applied mathematics. Numerical algorithms approximate intractable quantities from computable ones. They estimate integrals from evaluations of the integrand, or the path of a dynamical system described by differential equations from evaluations of the vector field. In other words, they infer a latent quantity from data. This book shows that it is thus formally possible to think of computational routines as learning machines, and to use the notion of Bayesian inference to build more flexible, efficient, or customised algorithms for computation. The text caters for Masters'' and PhD students, as well as postgraduate researchers in artificial intelligence, computer science, statistics, and applied mathematics. Extensive background material is provided along with a wealth of figures, worked examples, and exercises (with solutions) to develop intuition.

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Specifikationer
Sprog:
Engelsk
Sider:
410
ISBN-13:
9781107163447
Indbinding:
Hardback
Udgave:
ISBN-10:
1107163447
Kategori:
Udg. Dato:
30 jun 2022
Længde:
25mm
Bredde:
259mm
Højde:
211mm
Forlag:
Cambridge University Press
Oplagsdato:
30 jun 2022
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