Riemannian Deep Learning: Modules, Networks, and Geometries

arXiv:2607.19305v4 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