Séminaire FDD-FiME // X. Warin
Xavier Warin (EDF R&D)
Title : Mean-field neural networks: learning mappings on Wasserstein space
Abstract : We study the machine learning task for models with operators mapping between the Wasserstein space of probability measures and a space of functions, like e.g. in mean- field games/control problems. Different networks are proposed to learn these so-called mean-field functions, and are theoretically supported by universal approximation theorems. We perform several numerical experiments Read more [...]
