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Catalogue Information
Field name
Details
Dewey Class
620.11
Title
Bayesian Optimization for Materials Science ([EBook]) / by Daniel Packwood.
Author
Packwood, Daniel
Other name(s)
SpringerLink (Online service)
Publication
Singapore : Springer Singapore , 2017.
Physical Details
VIII, 42 pages, 16 illus., 12 illus. in color. : online resource.
Series
SpringerBriefs in the Mathematics of Materials
2365-6336 ; ; 3
ISBN
9789811067815
Summary Note
This book provides a short and concise introduction to Bayesian optimization specifically for experimental and computational materials scientists. After explaining the basic idea behind Bayesian optimization and some applications to materials science in Chapter 1, the mathematical theory of Bayesian optimization is outlined in Chapter 2. Finally, Chapter 3 discusses an application of Bayesian optimization to a complicated structure optimization problem in computational surface science. Bayesian optimization is a promising global optimization technique that originates in the field of machine learning and is starting to gain attention in materials science. For the purpose of materials design, Bayesian optimization can be used to predict new materials with novel properties without extensive screening of candidate materials. For the purpose of computational materials science, Bayesian optimization can be incorporated into first-principles calculations to perform efficient, global structure optimizations. While research in these directions has been reported in high-profile journals, until now there has been no textbook aimed specifically at materials scientists who wish to incorporate Bayesian optimization into their own research. This book will be accessible to researchers and students in materials science who have a basic background in calculus and linear algebra.:
Contents note
Chapter 1. Overview of Bayesian optimization in materials science -- Chapter 2. Theory of Bayesian optimization -- Chapter 3. Bayesian optimization of molecules adsorbed to metal surfaces.
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site
http://dx.doi.org/10.1007/978-981-10-6781-5
Links to Related Works
Subject References:
Energy Materials
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Materials science
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Statistical Physics and Dynamical Systems
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Statistical Theory and Methods
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Statistics
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Authors:
Packwood, Daniel
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Corporate Authors:
SpringerLink (Online service)
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Series:
SpringerBriefs in the Mathematics of Materials
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Classification:
620.11
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620.11
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