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Book synopsis

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.

Book details

Book category Books in German Naturwissenschaften, Medizin, Informatik, Technik Physik, Astronomie Thermodynamik Stoffmenge, Temperatur, Thermische

• Full title: Data-Based Methods for Materials Design and Discovery
• Author: Turab Lookman, James E. Gubernatis, Prasanna V. Balachandran
• Language: English
• Binding: Paperback
• Number of pages: 172
• EAN: 9783031012556
• ISBN: 3031012550
• ID: 39302301
• Publisher: Springer International Publishing AG
• Weight: 372 g
• Dimensions: 235 × 191 × 11 mm
• Date of publishing: 06. March 2020

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