Learning invariant representations of molecules for atomization energy prediction

Advances in Neural Information Processing Systems

Volumn 1, Issue , 2012, Pages 440-448

  Montavon, Grègoire ^a   Hansen, Katja ^b   Fazli, Siamac ^a   Rupp, Matthias ^c   Biegler, Franziska ^a   Ziehe, Andreas ^a   Tkatchenko, Alexandre ^b   Von Lilienfeld, O Anatole ^d   Müller, Klaus Robert ^a,e  

^a TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

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

^c ETH ZURICH   (Switzerland)

^d ARGONNE NATIONAL LABORATORY   (United States)

^e Korea University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURATE PREDICTION; ATOMIZATION ENERGIES; INVARIANT REPRESENTATION; MACHINE LEARNING PROBLEM; MOLECULAR ENERGIES; MOLECULAR GEOMETRIES; QUANTUM MECHANICAL; RATIONAL COMPOUND DESIGNS;

CHEMICAL COMPOUNDS;

EID: 84877770101     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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