New preprint
July 23, 2025
We published a new preprint on “Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime”.
I’m a 3rd year PhD student at the Department of Mathematics and Applications of ENS Ulm in Paris, working under the supervision of Gabriel Peyré and François-Xavier Vialard. This work is part of the Noria and Wolf ERC projects.
Research Interests
My research field is theoretical Machine Learning: I study the mathematical properties of large-scale algorithms for solving problems in optimization, sampling and learning. In my PhD I use tools from the theory of optimization, optimal control and optimal transport to study the convergence of gradient based algorithm in the training of overparameterized neural network architectures such as deep ResNets.
In a broader picture, I’m interested in the mathematics of Machine Learning and Data Science because one can find there a variety of open problems lying at the intersection between various fields of mathematics and with practical real-world applications.
Posts and news
Paper accepted at CPAM
July 23, 2025
I am very proud to announce that our paper on “Understanding the training of infinitely deep and wide ResNets with Conditional Optimal Transport” has been accepted for publication in Communications on Pure and Applied Mathematics.
Neurips 2022
November 28, 2022
I’ll be attending in person to the 36th Neurips conference in New Orleans, and will have the opportunity to present my work about “Global convergence of ResNets”.