Preprint
Sep 2026
Risk comparison theorems and application to deep learning of diffusion coefficients
This work investigates the nonparametric estimation of the diffusion matrix in stochastic differential equations featuring multidimensional, strong mixing covariate processes and proposes a flexible statistical framework that does not require a linear basis representation.
A. Gloter, Nakahiro Yoshida
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