r−adaptive meshes using Deep Neural Networks for solving Partial Differential Equations

  1. Angel J. Omella 1
  2. David Pardo 1
  1. 1 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

Livre:
Congress on Numerical Methods in Engineering CMN 2022 (2022. Las Palmas de Gran Canaria)
  1. David Greiner (ed. lit.)
  2. Irene Arias, (ed. lit.)
  3. Manuel Tur (ed. lit.)
  4. Gil Andrade-Campos (ed. lit.)
  5. Nuno Lopes (ed. lit.)
  6. J. Alexandre Pinho-da-Cruz (ed. lit.)

Éditorial: International Center for Numerical Methods in Engineering (CIMNE)

ISBN: 978-84-123222-9-3

Année de publication: 2022

Pages: 286-286

Congreso: Congress on Numerical Methods in Engineering (1. 2022. Las Palmas de Gran Canaria)

Type: Communication dans un congrès

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La source de données: Dialnet