Scheduled presentations:

• Non-diffusive neural network method for hyperbolic conservation laws
  *E. Lorin (Carleton University)
• Student Physics-Informed Neural Networks for Solving the Shallow-Water Equations
  *M. Mullins (École de technologie supérieure), A. Soulaïmani (École de technologie supérieure)
• Hybrid physics-informed neural network based multiscale solver for multi-fidelity upscaling operator learning
  *D. Korolev (Weierstrass Institute (WIAS)), M. Hintermüller (Weierstrass Institute (WIAS))
• Student Application of Physics-Informed Neural Networks in The Nonlinear Dynamic Analysis of Space Trusses
  P. de Mattos Pimenta (University of São Paulo), *L. Fernando Alves Macedo (University of São Paulo)
• Student Linear Operator Learning using GreenONets and a Multi-level Neural Network approach
  *C. Bilodeau (Polytechnique Montréal), Z. Aldirany (Polytechnique Montréal), R. Cottereau (Aix-Marseille Université, CNRS, LMA UMR 7031), S. Prudhomme (Polytechnique Montréal)
• Student Deep Neural Operators for Inversion and Surrogate Modeling in Unsaturated Flow
  *H. Kamil (University Mohammed VI Polytechnic), A. Soulaïmani (École de technologie supérieure), A. Beljadid (University Mohammed VI Polytechnic)