Simulating Complex Environments

This project will look at complex computer simulations, which are used to model complicated physical, chemical or biological phenomena, and seek to improve their analysis by using the geometry or topology of the parameter space (of the computational model) or the data, with application to various data driven deep learning models.

Programmes : IA acceptable & certifiable
Thèmes : apprentissages avec peu de données ou des données complexes, fair learning, IA et modèles physiques

Porteur :
Fabrice Gamboa, PR UT3