Welcome to my webpage !
Prior to that, I was a PhD student at Université Clermont Auvergne, under the supervision of Arnaud Guillin, Manon Michel and Boris Nectoux.
Research interests : Federated Learning, Particle systems, Mean-Field theory.
Papers :
Articles :
Law of Large Numbers for Bayesian two-layer Neural Network trained with Variational Inference, with Tom Huix, Arnaud Guillin, Manon Michel, Éric Moulines and Boris Nectoux, 36th Annual Conference on Learning Theory (COLT), 2023.
Law of large numbers and central limit theorem for wide two-layer neural networks: the mini-batch and noisy case, with Arnaud Guillin, Manon Michel and Boris Nectoux, To appear in the Journal of Machine Learning Research, 2022.
Preprint :
Central Limit Theorem for Bayesian Neural Network trained with Variational Inference, with Tom Huix, Arnaud Guillin, Manon Michel, Éric Moulines and Boris Nectoux, 2024.
Phd dissertation : Vers une compréhension mathématique des réseaux neuronaux profonds par une analyse champ moyen, 2023.