Fast and accurate modeling of molecular atomization energies with machine learning

Physical Review Letters

Volumn 108, Issue 5, 2012, Pages

  Rupp, Matthias ^a,b   Tkatchenko, Alexandre ^b,c   Müller, Klaus Robert ^a,b   Von Lilienfeld, O Anatole ^b,d  

^a TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c FRITZ HABER INSTITUT DER MAX PLANCK GESELLSCHAFT   (Germany)

^d ARGONNE NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURATE MODELING; ATOMIC POSITIONS; ATOMIZATION ENERGIES; CROSS VALIDATION; DINGER EQUATION; HYBRID DENSITY-FUNCTIONAL THEORY; MACHINE-LEARNING; MEAN ABSOLUTE ERROR; MOLECULAR ATOMIZATION ENERGIES; NUCLEAR CHARGES; ORGANIC MOLECULES; POTENTIAL ENERGY CURVES; REDUCED COMPLEXITY; REGRESSION MODEL; STATISTICAL REGRESSION;

DENSITY FUNCTIONAL THEORY; LEARNING SYSTEMS; NONLINEAR EQUATIONS; POTENTIAL ENERGY; REGRESSION ANALYSIS;

ATOMIZATION;

EID: 84856512353     PISSN: 00319007     EISSN: 10797114     Source Type: Journal    
DOI: 10.1103/PhysRevLett.108.058301     Document Type: Article

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