Scientific theories describe observations by equations with a small number of parameters or dimensions. Memory and computational efficiency of dimension reduction procedures is a function of the size ...

Unveiling physical laws from data is seen as the ultimate sign of human intelligence. While there is a growing interest in this sense around the machine learning community, some recent works have ...

In this article we describe a method that works to recover a parametrization for data lying on a manifold that is locally isometric to an open, connected subset Θ of Euclidean space ℝ d. Because this ...