Scheduled presentations:

• PIKS: Universal Phyisics Informed Kernel Methods
  J. Bona-Pellissier (UniGe), G. Meanti (UniGe), M. Santacesaria (UniGe), *L. Rosasco (UniGe)
• Optimal sampling and natural gradient for fast online learning in non-linear reduced order models
  A. Nouy (Ecole Central de Nantes), J. Soffo (Ecole Central de Nantes), *A. Somacal (Ecole Central de Nantes)
• Probabilistic neural operators for functional uncertainty quantification
  *C. Bülte (Ludwig-Maximilians-Universität München), P. Scholl (Ludwig-Maximilians-Universität München), G. Kutyniok (Ludwig-Maximilians-Universität München)
• Enhanced surrogate modelling via Autodecoders and Neural ODEs
  F. Regazzoni (MOX Laboratory, Politecnico di Milano), *G. Ziarelli (MOX Laboratory, Politecnico di Milano)
• Symmetric Convolutional AutoEncoders for Model Order Reduction
  *G. Li Causi (SISSA), N. Tonicello (SISSA), L. Magri (Imperial College London), G. Rozza (SISSA)
• Bridging Low- and High-Fidelity Simulations of Parametrized Time-Dependent PDEs with Multi-Fidelity Neural Operators
  *M. Migliavacca (Politecnico di Milano), A. Manzoni (Politecnico di Milano), A. Frangi (Politecnico di Milano)