From Layers to Networks: Comparing Neural Representations via Diffusion Geometry
DGX agentarXiv:2605.15901v1 Announce Type: new Abstract: Diffusion geometry is a manifold learning framework that uses random walks defined by Markov transition matrices to characterize the geometry of a datas