Bayesian Optimization for Materials Science
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...
Main Author: | Packwood, Daniel. (Author, http://id.loc.gov/vocabulary/relators/aut) |
---|---|
Corporate Author: | SpringerLink (Online service) |
Language: | English |
Published: |
Singapore :
Springer Singapore : Imprint: Springer,
2017.
|
Edition: | 1st ed. 2017. |
Series: | SpringerBriefs in the Mathematics of Materials,
3 |
Subjects: | |
Online Access: | https://doi.org/10.1007/978-981-10-6781-5 |
Similar Items
-
Electronic Characterisation of Earth‐Abundant Sulphides for Solar Photovoltaics by Thomas James Whittles.
by: Whittles, Thomas James., et al.
Published: (2018) -
Materials Development for Active/Passive Components of a Supercapacitor Background, Present Status and Future Perspective / by Aneeya K. Samantara, Satyajit Ratha.
by: Samantara, Aneeya K., et al.
Published: (2018) -
Advances in Silicon Solar Cells edited by Shadia Ikhmayies.
Published: (2018) -
Fatigue of Materials at Very High Numbers of Loading Cycles Experimental Techniques, Mechanisms, Modeling and Fatigue Life Assessment / edited by Hans-Jürgen Christ.
Published: (2018) -
Energy Technology 2018 Carbon Dioxide Management and Other Technologies / edited by Ziqi Sun, Cong Wang, Donna Post Guillen, Neale R Neelameggham, Lei Zhang, John A. Howarter, Tao Wang, Elsa Olivetti, Mingming Zhang, Dirk Verhulst, Xiaofei Guan, Allie Anderson, Shadia Ikhmayies, York R. Smith, Amit Pandey, Sarma Pisupati, Huimin Lu.
Published: (2018)