Machine Learning in Molecular Sciences (Challenges and Advances in Computational Chemistry and Physics, 36, Band 36) - Hardcover

 
9783031371950: Machine Learning in Molecular Sciences (Challenges and Advances in Computational Chemistry and Physics, 36, Band 36)
Hardcover
ISBN 10: 303137195X ISBN 13: 9783031371950
Verlag: Springer, 2023

Inhaltsangabe

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.

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Über die Autorin bzw. den Autor

Chen Qu is currently a research associate of National Institute of Standards and Technology. His current research focuses on applying machine learning methods to predict important chemical properties such as gas chromatography retention indices and mass spectra. He received his Ph.D. at Emory University, where he conducted research primarily on machine learning potential energy surfaces, under the guidance of Prof. Joel Bowman.  


Hanchao Liu is currently a machine learning engineer at Google. His work focuses on building large-scale machine learning infrastructures and platforms. Dr. Liu received his Ph.D. in computational chemistry at Emory University under the tutelage of Prof. Joel Bowman, where he applied computational and machine learning methods to study the vibrational dynamics and spectra of various forms of water.

Von der hinteren Coverseite

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.

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Verlag
Springer
Erscheinungsdatum
2023
Sprache
Englisch
ISBN 10 
303137195X
ISBN 13 
9783031371950
Einband
Gebundene Ausgabe
Anzahl der Seiten
327
Herausgeber
Qu Chen, Liu Hanchao
Kontakt zum Hersteller
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Deutschland

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9783031371981: Machine Learning in Molecular Sciences (Challenges and Advances in Computational Chemistry and Physics, Band 36)

Vorgestellte Ausgabe

ISBN 10:  3031371984 ISBN 13:  9783031371981
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