2017
Principles of Riemannian Geometry in Neural Networks
NeurIPS 2017poster
This study deals with neural networks in the sense of geometric transformations acting on the coordinate representation of the underlying data manifold which the data is sampled from. It forms part of an attempt to construct a formalized general theory of neural networks in the setting of Riemannian…