arXiv cs.AI
· Papers
Riemannian Deep Learning: Modules, Networks, and Geometries
arXiv:2607.19305v3 Announce Type: replace-cross Abstract: Deep neural networks on manifold-valued representations have attracted growing interest, but many basic components remain tied to specific manifolds, rely on Euclidean approximations, or require costly and numerically fragile geometric operations. This thesis de