Séminaire FDD-FiME // X. Warin

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Séminaire FDD-FiME // X. Warin

21 avril @ 14 h 00 min - 15 h 00 min

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 for training these mean-field neural networks, and show their accuracy and efficiency in the generalization error with various test distributions. Finally, we present different algorithms relying on mean-field neural networks for solving time-dependent mean-field problems.

A Joint work with Huyên Pham.

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Date :
21 avril
Heure :
14 h 00 min - 15 h 00 min


Institut Henri Poincaré