Bayesian non-parametric analysis of diffusions

This presentation will describe recent progress on Bayesian non-parametric analysis of diffusion drift functions given continuous data on a finite time interval. It turns out that Gaussian processes can be used as conjugate priors, and we describe methodology for characterising posterior mean and covariance structure in terms of solutions to differential equations with coefficients given as functions of the observed diffusion local time.