A probabilistic view on Riemannian machine learning models for SPD matrices

Thibault de Surrel, Florian Yger, Fabien Lotte +1

The goal of this paper is to show how different machine learning tools on the Riemannian manifold ${\mathcal{P}}_d$ of Symmetric Positive Definite (SPD) matrices can be united under…