3 papers
math.PR2026
Universality in Deep Neural Networks: An approach via the Lindeberg exchange principle
Filippo Giovagnini, Sotirios Kotitsas, Marco Romito
We consider the infinite-width limit of a fully connected deep neural network with general weights, and we prove quantitative general bounds on the -Wasserstein distance between…
math.PR2025
Edwards-Wilkinson limit for a stochastic advection-diffusion PDE
Sotirios Kotitsas, Dejun Luo, Mario Maurelli
We consider a diffusion in a Gaussian random environment that is white in time and study the large-scale behavior of the quenched density with respect to the Lebesgue measure. We s…
math.PR2025
The heat equation with time-correlated random potential in d=2: Edwards-Wilkinson fluctuations
Sotirios Kotitsas
We consider the stochastic PDE: in dimension , where the potential V is the space and time mollification of the two-di…