3 papers
math.PR2026
Gradient Mean-Field Dynamics with Measure-Valued States: Well-Posedness, Chaos, and Long-Time Stability
Anderson Melchor Hernandez
We study a stochastic mean-field interacting particle system whose state space is $\Y = \Tt^d \times \cP(U)$, where the first component represents a spatial variable and the second…
quant-ph2026
On a Central Limit Theorem and Sanov's principle for quantum neural networks
Anderson Melchor Hernandez
In this work, we study the fluctuations of a Mixture of Experts (MoE) generated by a quantum neural network trained via gradient flow on supervised learning problems. Our main resu…
math.PR2023
-convergence of discrete energies modeling self-aggregation of stochastic particles
Luca Lussardi, Anderson Melchor Hernandez, Marco Morandotti
In this work, we demonstrate that a functional modeling the self-aggregation of stochastically distributed lipid molecules can be obtained as the -limit of a family of discrete…