We study the Bayesian density estimation of data living in the offset of an unknown
submanifold of the Euclidean space. In this perspective, we introduce a new notion of …

In high-dimensional statistics, the manifold hypothesis presumes that the data lie near low-
dimensional structures, called manifolds. This assumption helps explain why machine …

This work studies nonparametric Bayesian estimation of the intensity function of an
inhomogeneous Poisson point process in the important case where the intensity depends …

Bayesian Statistics has been increasingly popular in the last five decades. Besides having
decision theoretic foundation, the Bayesian approach found popularity thanks to the simple …