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A data-centric approach to generative modelling for 3D-printed steel.
Dodwell, T J; Fleming, L R; Buchanan, C; Kyvelou, P; Detommaso, G; Gosling, P D; Scheichl, R; Kendall, W S; Gardner, L; Girolami, M A; Oates, C J.
Afiliação
  • Dodwell TJ; Institute of Data Science and AI, University of Exeter, Exeter EX4 4QJ, UK.
  • Fleming LR; The Alan Turing Institute, London NW1 2DB, UK.
  • Buchanan C; School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.
  • Kyvelou P; The Alan Turing Institute, London NW1 2DB, UK.
  • Detommaso G; Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK.
  • Gosling PD; Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK.
  • Scheichl R; Amazon Core AI, Berlin, Germany.
  • Kendall WS; School of Engineering, Heidelberg University, Heidelberg 69120, Germany.
  • Gardner L; Institute of Applied Mathematics, Heidelberg University, Heidelberg 69120, Germany.
  • Girolami MA; Department of Statistics, University of Warwick, Coventry CV4 7AL, UK.
  • Oates CJ; The Alan Turing Institute, London NW1 2DB, UK.
Proc Math Phys Eng Sci ; 477(2255): 20210444, 2021 Nov.
Article em En | MEDLINE | ID: mdl-35153595
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

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