  In this paper we tackle the problem of comparing distributions of random
variables and defining a mean pattern between a sample of random events. Using
barycenters of measures in the Wasserstein space, we propose an iterative
version as an estimation of the mean distribution. Moreover, when the
distributions are a common measure warped by a centered random operator, then
the barycenter enables to recover this distribution template.
