MS029A Physics-based Surrogate Models and Scientific Machine Learning
Main Organizer:
Dr.
Davide Torlo
(
Università di Roma La Sapienza
, Italy
)
Chaired by:
Dr. Francesco Regazzoni (Politecnico di Milano , Italy) , Dr. Federico Pichi (SISSA , Italy)
Dr. Francesco Regazzoni (Politecnico di Milano , Italy) , Dr. Federico Pichi (SISSA , Italy)
Scheduled presentations:
-
Structure-preserving neural network surrogates for kinetic equations with uncertainty
-
Enhancing topology optimisation pipelines via machine learning surrogates
-
Reinforcement Learning for Filter-Based Regularization of Convection-Dominated Flows
-
Advanced Optimal Transport Strategies for Efficient Computation and Reduced Order Modeling in Complex Systems
-
Patient-specific Prediction of Glioblastoma Growth via Reduced Order Modeling and Neural Networks
-
Accelerating Natural Gradient Descent for PINNs with Randomized Numerical Linear Algebra
