Machine Learning in Molecular Sciences (eBook)

Chen Qu, Hanchao Liu (Herausgeber)

eBook Download: PDF

2023
317 Seiten
Springer International Publishing (Verlag)
978-3-031-37196-7 (ISBN)

Infos

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.

Produkt-Details

• Erscheint lt. Verlag: 1.10.2023
• Reihe/Serie: Challenges and Advances in Computational Chemistry and Physics
• Reihe/Serie: Challenges and Advances in Computational Chemistry and Physics
• Zusatzinfo: X, 317 p. 80 illus., 74 illus. in color.
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Naturwissenschaften ► Biologie
• Themenwelt: Naturwissenschaften ► Chemie
• Schlagworte: Artificial Intelligence • chemical kinetics • Deep learning • density functional theory • Electronic structure theory • graph neural networks • machine learning • Molecular Sciences • organic synthesis • potential energy surface • Protein Engineering • Voxelized Representations
• ISBN-10: 3-031-37196-8 / 3031371968
• ISBN-13: 978-3-031-37196-7 / 9783031371967