arxivcs.LGcs.AImath.DG2026-07-21
Riemannian Deep Learning: Modules, Networks, and Geometries
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 develops a unified f…