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Gaussian Process Regression for Materials and Molecules.
Deringer, Volker L; Bartók, Albert P; Bernstein, Noam; Wilkins, David M; Ceriotti, Michele; Csányi, Gábor.
Afiliação
  • Deringer VL; Department of Chemistry, Inorganic Chemistry Laboratory, University of Oxford, Oxford OX1 3QR, United Kingdom.
  • Bartók AP; Department of Physics and Warwick Centre for Predictive Modelling, School of Engineering, University of Warwick, Coventry CV4 7AL, United Kingdom.
  • Bernstein N; Center for Computational Materials Science, U.S. Naval Research Laboratory, Washington D.C. 20375, United States.
  • Wilkins DM; Atomistic Simulation Centre, School of Mathematics and Physics, Queen's University Belfast, Belfast BT7 1NN, Northern Ireland, United Kingdom.
  • Ceriotti M; Laboratory of Computational Science and Modeling, IMX, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland.
  • Csányi G; National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Chem Rev ; 121(16): 10073-10141, 2021 08 25.
Article em En | MEDLINE | ID: mdl-34398616
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Chem Rev Ano de publicação: 2021 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Chem Rev Ano de publicação: 2021 Tipo de documento: Article