Machine Learning in Chemistry
The Impact of Artificial Intelligence
Theoretical and Computational Chemistry Series
Editor-in-chief:
Jonathan Hirst, University of Nottingham, Nottingham, UK
Advisory board:
Dongqing Wei, Shanghai Jiao Tong University, China
Jeremy Smith, Oakridge National Laboratory, USA
Titles in the series:
1: Knowledge-based Expert Systems in Chemistry: Not Counting on Computers
2: Non-Covalent Interactions: Theory and Experiment
3: Single-Ion Solvation: Experimental and Theoretical Approaches to Elusive Thermodynamic Quantities
4: Computational Nanoscience
5: Computational Quantum Chemistry: Molecular Structure and Properties in Silico
6: Reaction Rate Constant Computations: Theories and Applications
7: Theory of Molecular Collisions
8: In Silico Medicinal Chemistry: Computational Methods to Support Drug Design
9: Simulating Enzyme Reactivity: Computational Methods in Enzyme Catalysis
10: Computational Biophysics of Membrane Proteins
11: Cold Chemistry: Molecular Scattering and Reactivity Near Absolute Zero
12: Theoretical Chemistry for Electronic Excited States
13: Attosecond Molecular Dynamics
14: Self-organized Motion: Physicochemical Design based on Nonlinear Dynamics
15: Knowledge-based Expert Systems in Chemistry: Artificial Intelligence in Decision Making
16: London Dispersion Forces in Molecules, Solids, and Nano-structures: An Introduction to Physical Models and Computational Methods
17: Machine Learning in Chemistry: The Impact of Artificial Intelligence
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Machine Learning in Chemistry
The Impact of Artificial Intelligence
Edited by
Hugh M. Cartwright
Oxford University, UK
Email: [email protected]
Theoretical and Computational Chemistry Series No. 17
Print ISBN: 978-1-78801-789-3
PDF ISBN: 978-1-83916-023-3
EPUB ISBN: 978-1-83916-024-0
Print ISSN: 2041-3181
Electronic ISSN: 2041-319X
A catalogue record for this book is available from the British Library
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