Scheduled presentations:

• Two-level preconditioning with Neural Green's Operators
  *H. Melchers (Eindhoven University of Technology), J. Prins (Eindhoven University of Technology), M. Abdelmalik (Eindhoven University of Technology)
• Sparse domain decomposition method for large neural networks
  *B. Rosic (TU Wien), T. Godde (University of Twente)
• Modelling stochastic, anisotropic material tensors by spatially-decomposed neural networks
  *T. Gödde (University of Twente), B. Rosić (University of Twente)
• Demonstration of a Modular Library of Learned Operators for the Composition of Partial Differential Equation Solutions
  *E. Kostas (University of Patras), A. Lachanas (University of Patras), T. Gortsas (University of Patras), P. Papadopoulos (University of Patras)
• A Hybrid Framework for Coupled Multi-Domain Structural Analysis with Neural Operators
  *C. Lyoo (Korea University), M. Yu (Korea University), G. Noh (Korea University)
• Operator Learning for Long-Time Prediction of Nonlinear Partial Differential Equations
  *F. Tokmukhamedova (La Rochelle University), J. Lux (La Rochelle University), C. Allery (La Rochelle University)