Abstract: The development of PDE models capable of describing tumor growth may help to monitor disease progression or predict the efficacy of different therapeutic strategies. However, to be truly informative or predictive, these models need to be corrected and/or parameterized
Abstract : Self-similar solutions for the modified Korteweg-de Vries equation are of both physical and mathematical interest. On the physical side, among several applications, they model the formation of sharp corners in planar vortex patches. Mathematically, they describe the asymptotic
We study data-dependent uniform generalization bounds by approaching the problem from a PAC-Bayesian perspective. We first apply the PAC-Bayesian framework on ``random sets'' in a rigorous way, where the training algorithm is assumed to output a data-dependent hypothesis set after
Neural network compression has been an increasingly important subject, not only due to its practical relevance, but also due to its theoretical implications, as there is an explicit connection between compressibility and generalization error. In this talk, I will present
L'écriture des nombres réels dans une base entière est source de nombreuses questions, tant élémentaires dans leurs formulations que difficiles dans leurs résolutions. Est-il vrai que tous les chiffres apparaissent infiniment souvent dans l'écriture décimale de \(\pi\), de \(e\), de
