Intern, Apple
2 papers at NeurIPS 2025
We study the Schrodinger bridge problem with a general Ornstein-Uhlenbeck reference dynamics that allows for modelling of non-equilibrium dynamics.
We consider the problem of learning drift, diffusion and growth rate from snapshot observations of a population of individuals that may divide or die, and propose a novel inference scheme to learn these terms from data.
