Machine Learning in Molecular Sciences Machine Learning in Molecular Sciences
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Beschreibung des Verlags

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.

GENRE
Wissenschaft und Natur
ERSCHIENEN
2023
1. Oktober
SPRACHE
EN
Englisch
UMFANG
327
Seiten
VERLAG
Springer International Publishing
GRÖSSE
38
 MB
Emerging Materials and Environment Emerging Materials and Environment
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Semiclassical Nonadiabatic Molecular Dynamics Semiclassical Nonadiabatic Molecular Dynamics
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Materials Informatics II Materials Informatics II
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Materials Informatics III Materials Informatics III
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Non-Linear Optical Properties of Matter Non-Linear Optical Properties of Matter
2007