Solving Partial Differential Equations using Adversarial Neural Networks

  1. Carlos Uriarte 1
  2. David Pardo 1
  3. Judit Muñoz-Matute 2
  4. Ignacio Muga 3
  1. 1 University of the Basque Country (UPV/EHU)
  2. 2 Basque Center for Applied Mathematics ( Spain)
  3. 3 Pontificia Universidad Católica de Valparaíso (Chile)
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Buch:
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.)

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

ISBN: 978-84-123222-9-3

Datum der Publikation: 2022

Seiten: 289-289

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

Art: Konferenz-Beitrag

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Fuente de los datos: Dialnet