2020
State-Space Gaussian Process for Drift Estimation in Stochastic Differential Equations
ICASSP 2020accepted
This paper is concerned with the estimation of unknown drift functions of stochastic differential equations (SDEs) from observations of their sample paths. We propose to formulate this as a non-parametric Gaussian process regression problem and use an Ito-Taylor expansion for approximating the SDE.…