Tribute to Stephen Hawking – From Stars to Neurosciences

Blind Source Separation & Riemannian Geometry Classification

Thanks Stephen Hawking for your wonderful contributions to humankind. When I was 14, you explained me the concepts of relativity and entropy with your book “A Brief History of Time” and it changed everything for me, especially the way I’ll understand Neurosciences and Brain-Computer Interfaces. Who knows that several years later, I would work in […]

Using Riemannian Geometry for Source Separation

Finding hidden variables in data can be challenging. Using Blind Source Separation allows to exact the independent sources in a unsupervised way. However, the methods require usually strong optimization constraints in order to avoid degenerate solutions and/or improve convergence. By using Riemannian Geometry framework, we propose to use the geometrical properties of the manifold that […]