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The Resource Bayesian optimization for materials science, Daniel Packwood

Bayesian optimization for materials science, Daniel Packwood

Label
Bayesian optimization for materials science
Title
Bayesian optimization for materials science
Statement of responsibility
Daniel Packwood
Creator
Subject
Language
eng
Summary
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
Member of
http://library.link/vocab/creatorName
Packwood, Daniel
Dewey number
519.6
Index
no index present
Literary form
non fiction
Nature of contents
dictionaries
Series statement
SpringerBriefs in the Mathematics of Materials,
Series volume
3
http://library.link/vocab/subjectName
  • Mathematical optimization
  • Materials
  • Materials science
Label
Bayesian optimization for materials science, Daniel Packwood
Instantiates
Publication
Bibliography note
Includes bibliographical references
Contents
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
Control code
on1021273019
Dimensions
unknown
Extent
1 online resource
Form of item
online
Isbn
9789811067815
Note
SpringerLink
Specific material designation
remote
System control number
(OCoLC)1021273019
Label
Bayesian optimization for materials science, Daniel Packwood
Publication
Bibliography note
Includes bibliographical references
Contents
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
Control code
on1021273019
Dimensions
unknown
Extent
1 online resource
Form of item
online
Isbn
9789811067815
Note
SpringerLink
Specific material designation
remote
System control number
(OCoLC)1021273019

Library Locations

    • InternetBorrow it
      Albany, Auckland, 0632, NZ
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