activity
20162020
most citedThe mean field Schrödinger problem: ergodic behavior, entropy estimates and functional inequalities

4 citations · 6 across the 4 of their papers we have counts for

collaborators

10 papers

math.CA2020

On the variational interpretation of local logarithmic Sobolev inequalities

Gauthier Clerc, Giovanni Conforti, Ivan Gentil

The celebrated Otto calculus has established itself as a powerful tool for proving quantitative energy dissipation estimates and provides with an elegant geometric interpretation o…

math.PR2020

A probabilistic approach to convex -entropy decay for Markov chains

Giovanni Conforti

We study the exponential dissipation of entropic functionals for continuous time Markov chains and the associated convex Sobolev inequalities, including MLSI and Beckner inequaliti…

cs.GT2020

Game on Random Environment, Mean-field Langevin System and Neural Networks

Giovanni Conforti, Anna Kazeykina, Zhenjie Ren

In this paper we study a type of games regularized by the relative entropy, where the players' strategies are coupled through a random environment variable. Besides the existence a…

math.PR2019

A formula for the time derivative of the entropic cost and applications

Giovanni Conforti, Luca Tamanini

In the recent years the Schrödinger problem has gained a lot of attention because of the connection, in the small-noise regime, with the Monge-Kantorovich optimal transport problem…

math.PR20194 cited

The mean field Schrödinger problem: ergodic behavior, entropy estimates and functional inequalities

Julio Backhoff-Veraguas, Giovani Conforti, Ivan Gentil +1

We study the mean field Schrödinger problem (MFSP), that is the problem of finding the most likely evolution of a cloud of interacting Brownian particles conditionally on the obser…

math.OC2019

Multi-marginal Schrodinger bridges

Yongxin Chen, Giovanni Conforti, Tryphon T. Georgiou +1

We consider the problem to identify the most likely flow in phase space, of (inertial) particles under stochastic forcing, that is in agreement with spatial (marginal) distribution…