Learning stochasticity via a nonparametric approach to state-dependent noise estimation
Modeling stochastic dynamical systems remains a central challenge across disciplines. Incomplete knowledge of nonlinear interactions and state-dependent fluctuations often renders bottom-up approaches ineffective, motivating methods that infer governing equations directly from data. However, parametric models struggle...