activity
20052024
most citedA Mass Transportation Model for the Optimal Planning of an Urban Region

68 citations · 321 across the 52 of their papers we have counts for

collaborators

61 papers

math.AP2024

On Optimal Transport Maps Between 1 /d-Concave Densities

Guillaume Carlier, Alessio Figalli, Filippo Santambrogio

In this paper, we extend the scope of Caffarelli's contraction theorem, which provides a measure of the Lipschitz constant for optimal transport maps between log-concave probabilit…

math.AP2023

New Lipschitz estimates and long-time asymptotic behavior for porous medium and fast diffusion equations

Noemi David, Filippo Santambrogio

We obtain new estimates for the solution of both the porous medium and the fast diffusion equations by studying the evolution of suitable Lipschitz norms. Our results include insta…

math.PR2023★ 3 cited

Uniform contractivity of the Fisher infinitesimal model with strongly convex selection

Vincent Calvez, David Poyato, Filippo Santambrogio

The Fisher infinitesimal model is a classical model of phenotypic trait inheritance in quantitative genetics. Here, we prove that it encompasses a remarkable convexity structure wh…

math.OC2022

Strong convergence of the JKO scheme for the Fokker-Planck equation

Filippo Santambrogio, Gayrat Toshpulatov

Following a celebrated paper by Jordan, Kinderleherer and Otto it is possible to discretize in time the Fokker-Planck equation b…

math.AP2021★ 3 cited

A cross-diffusion system obtained via (convex) relaxation in the JKO scheme

Romain Ducasse, Filippo Santambrogio, Havva Yoldaş

In this paper, we start from a very natural system of cross-diffusion equations, which can be seen as a gradient flow for the Wasserstein distance of a certain functional. Unfortun…

math.OC2021★ 2 cited

Non-asymptotic convergence bounds for Wasserstein approximation using point clouds

Quentin Merigot, Filippo Santambrogio, Clément Sarrazin

Several issues in machine learning and inverse problems require to generate discrete data, as if sampled from a model probability distribution. A common way to do so relies on the…