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International Journal of Quantum Chemistry

Volumn 115, Issue 16, 2015, Pages 1084-1093

Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties

(4) Von Lilienfeld, O Anatole a,b Ramakrishnan, Raghunathan a Rupp, Matthias a Knoll, Aaron b,c

a UNIVERSITY OF BASEL (Switzerland)

b ARGONNE NATIONAL LABORATORY (United States)

c UNIVERSITY OF TEXAS AT AUSTIN (United States)

Author keywords

descriptor; machine learning; molecules; quantum chemistry; representation

Indexed keywords

ATOMIZATION; ATOMS; CHEMICAL BONDS; DISTRIBUTION FUNCTIONS; ENTHALPY; FOURIER SERIES; LEARNING SYSTEMS; MACHINE LEARNING; MOLECULES; QUANTUM CHEMISTRY; SUPERCONDUCTING MATERIALS;

ATOMIC RADIAL DISTRIBUTION FUNCTIONS; DESCRIPTORS; FINGERPRINT REPRESENTATION; MACHINE LEARNING MODELS; MOLECULAR ENTHALPIES; MOLECULAR FINGERPRINT; MOLECULAR REPRESENTATIONS; REPRESENTATION;

STEREOCHEMISTRY;

EID: 84936800622 PISSN: 00207608 EISSN: 1097461X Source Type: Journal
DOI: 10.1002/qua.24912 Document Type: Article

Times cited : (239)

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