FCHL revisited: Faster and more accurate quantum machine learning-Reference-Cited by-同舟云学术

FCHL revisited: Faster and more accurate quantum machine learning

Published:2020-01-31 Issue:4 Volume:152 Page:044107
ISSN:0021-9606
Container-title:The Journal of Chemical Physics
language:en
Short-container-title:J. Chem. Phys.

Author:

Christensen Anders S.¹^ORCID,Bratholm Lars A.²³^ORCID,Faber Felix A.¹^ORCID,Anatole von Lilienfeld O.¹^ORCID

Affiliation:

1. Department of Chemistry, National Center for Computational Design and Discovery of Novel Materials (MARVEL), Institute of Physical Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland

2. School of Mathematics, University of Bristol, Bristol BS8 1TW, United Kingdom

3. School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom

Funder

Air Force Office of Scientific Research

Engineering and Physical Sciences Research Council

National Center of Competence in Research Materials’ Revolution: Computational Design and Discovery of Novel Materials

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5126701

Reference63 articles.

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5. Perspective: Machine learning potentials for atomistic simulations

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