Scheduled presentations:

• Finite element interpolated neural networks for forward and transient problems
  *S. Badia (Monash University), W. Li (Monash University), A. Martin (ANU)
• r-Adaptive Deep Learning PDE Solver With Triangular Meshes
  *Á. Omella (University of the Basque Country (UPV/EHU)), J. González-Sieiro (Basque Center for Applied Mathematics (BCAM)), T. Teijeiro (Basque Center for Applied Mathematics (BCAM)), D. Pardo (University of the Basque Country (UPV/EHU))
• A Discontinuous Deep Ritz Method for PDEs
  *M. Strugaru (BCAM), Á. Omella (UPV/EHU), D. Pardo (UPV/EHU, BCAM, and IKERBASQUE), I. Muga (PUCV)
• Enhancing OpenFOAM with Deep Learning for Minimising the Spatial Discretisation Error on Coarse Meshes
  *J. Gonzalez-Sieiro (Basque Center for Applied Mathematics), D. Pardo (Basque Center for Applied Mathematics), V. Nava (Basque Center for Applied Mathematics), V. Calo (Curtin University)
• A deep learning approach for the reconstuction of 3D geometries and fields
  *S. Pagani (Politecnico di Milano), D. Carrara (Politecnico di Milano), F. Regazzoni (Politecnico di Milano)
• A PDE-informed and Physics-informed neural network for learning weak solutions in two-dimensional conservation laws
  E. Abreu (Universidade Estadual de Campinas), *J. Florindo (Universidade Estadual de Campinas), W. Lambert (Federal University of Alfenas)