Machine Learning, Quantum Chemistry, and Chemical Space-Reference-Cited by-同舟云学术

Machine Learning, Quantum Chemistry, and Chemical Space

Published:2017-04-03 Issue: Volume: Page:225-256
ISSN:1934-5372
Container-title:Reviews in Computational Chemistry
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Author:

Ramakrishnan Raghunathan¹,von Lilienfeld O. Anatole¹²

Affiliation:

1. Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, Department of Chemistry; University of Basel; Basel Switzerland

2. General Chemistry; Free University of Brussels; Brussels Belgium

Publisher

John Wiley & Sons, Inc.

Reference111 articles.

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2. Navigating Chemical Space for Biology and Medicine;Lipinski;Nature,2004

3. Chemical Space and Biology;Dobson;Nature,2004

4. First Principles View on Chemical Compound Space: Gaining Rigorous Atomistic Control of Molecular Properties;von Lilienfeld;Int. J. Quantum Chem.,2013

5. K. Burke “Any Ab Initio method must either be void of empirical parameters, or at least have parameters that do not depend on the system being studied.” Oral communication, IPAM, UCLA 2011

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