In this talk we first review the theory of Dirichlet spaces, where one can develop regularity spaces and a wavelet system. This theory, for instance, applies to convex subsets of Riemannian manifolds. Then we revisit and generalize some classical results on the behavior of Gaussian processes and non-parametric adaptive statistical estimation.