5 papers
A new probabilistic approach for mean field games of optimal stopping
Andrea Cosso, Laura D'Andolfi, Roxana Dumitrescu
We propose a novel probabilistic formulation for optimal stopping mean field games (OS-MFGs) with randomized strategies. We characterize mean field equilibria through a new class o…
Calorimeter Shower Superresolution with Conditional Normalizing Flows: Implementation and Statistical Evaluation
Andrea Cosso
In High Energy Physics, detailed calorimeter simulations and reconstructions are essential for accurate energy measurements and particle identification, but their high granularity…
Mean convergence rates for Gaussian-smoothed Wasserstein distances and classical Wasserstein distances
Andrea Cosso, Mattia Martini, Laura Perelli
We establish upper bounds for the expected -th power of the Gaussian-smoothed -Wasserstein distance between a probability measure and the corresponding empirical measure…
Mean field optimal stopping with uncontrolled state
Andrea Cosso, Laura Perelli
We study a specific class of finite-horizon mean field optimal stopping problems by means of the dynamic programming approach. In particular, we consider problems where the state p…
On the optimal stopping problem for diffusions and an approximation result for stopping times
Andrea Cosso, Laura Perelli
In this article, we study the classical finite-horizon optimal stopping problem for multidimensional diffusions through an approach that differs from what is typically found in the…