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On scientific understanding with artificial intelligence.
Krenn, Mario; Pollice, Robert; Guo, Si Yue; Aldeghi, Matteo; Cervera-Lierta, Alba; Friederich, Pascal; Dos Passos Gomes, Gabriel; Häse, Florian; Jinich, Adrian; Nigam, AkshatKumar; Yao, Zhenpeng; Aspuru-Guzik, Alán.
Afiliação
  • Krenn M; Max Planck Institute for the Science of Light (MPL), Erlangen, Germany.
  • Pollice R; Chemical Physics Theory Group, Department of Chemistry, University of Toronto, Toronto, Ontario Canada.
  • Guo SY; Department of Computer Science, University of Toronto, Toronto, Ontario Canada.
  • Aldeghi M; Vector Institute for Artificial Intelligence, Toronto, Ontario Canada.
  • Cervera-Lierta A; Chemical Physics Theory Group, Department of Chemistry, University of Toronto, Toronto, Ontario Canada.
  • Friederich P; Department of Computer Science, University of Toronto, Toronto, Ontario Canada.
  • Dos Passos Gomes G; Chemical Physics Theory Group, Department of Chemistry, University of Toronto, Toronto, Ontario Canada.
  • Häse F; Chemical Physics Theory Group, Department of Chemistry, University of Toronto, Toronto, Ontario Canada.
  • Jinich A; Department of Computer Science, University of Toronto, Toronto, Ontario Canada.
  • Nigam A; Vector Institute for Artificial Intelligence, Toronto, Ontario Canada.
  • Yao Z; Chemical Physics Theory Group, Department of Chemistry, University of Toronto, Toronto, Ontario Canada.
  • Aspuru-Guzik A; Department of Computer Science, University of Toronto, Toronto, Ontario Canada.
Nat Rev Phys ; 4(12): 761-769, 2022.
Article em En | MEDLINE | ID: mdl-36247217

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Nat Rev Phys Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Nat Rev Phys Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha