Machine Learning in Molecular Sciences

Machine learning and artificial intelligence have propelled research across various molecular science disciplines thanks to the rapid progress in computing hardware, algorithms, and data accumulation. This book presents recent machine learning applications in the broad research field of molecular sc...

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Bibliographic Details
Other Authors: Qu, Chen (Editor), Liu, Hanchao (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2023, 2023
Edition:1st ed. 2023
Series:Challenges and Advances in Computational Chemistry and Physics
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Description
Summary:Machine learning and artificial intelligence have propelled research across various molecular science disciplines thanks to the rapid progress in computing hardware, algorithms, and data accumulation. This book presents recent machine learning applications in the broad research field of molecular sciences. Written by an international group of renowned experts, this edited volume covers both the machine learning methodologies and state-of-the-art machine learning applications in a wide range of topics in molecular sciences, from electronic structure theory to nuclear dynamics of small molecules, to the design and synthesis of large organic and biological molecules. This book is a valuable resource for researchers and students interested in applying machine learning in the research of molecular sciences
Physical Description:X, 317 p. 80 illus., 74 illus. in color online resource
ISBN:9783031371967