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Data-Based Methods for Materials Design and Discovery : Basic Ideas and General Methods

By: (Author) Ghanshyam Pilania , (Author) James E. Gubernatis , (Author) Prasanna V. Balachandran , (Author) Turab Lookman

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Ksh 8,100.00

Format: Paperback / Softback

ISBN-10: 3031012550

ISBN-13: 9783031012556

Series: Synthesis Lectures on Materials and Optics

Publisher: Springer International Publishing AG

Imprint: Springer International Publishing AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Mar 6th, 2020

Print length: 172 Pages

Product Classification: Laser physics
Materials science

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Machine learning methods are changing the way we design and discover new materials. This book provides an overview of approaches successfully used in addressing materials problems (alloys, ferroelectrics, dielectrics) with a focus on probabilistic methods, such as Gaussian processes, to accurately estimate density functions.
Machine learning methods are changing the way we design and discover new materials. This book provides an overview of approaches successfully used in addressing materials problems (alloys, ferroelectrics, dielectrics) with a focus on probabilistic methods, such as Gaussian processes, to accurately estimate density functions. The authors, who have extensive experience in this interdisciplinary field, discuss generalizations where more than one competing material property is involved or data with differing degrees of precision/costs or fidelity/expense needs to be considered.

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