AI RESEARCH

Riemannian Generative Decoder

arXiv CS.LG

ArXi:2506.19133v3 Announce Type: replace Euclidean representations distort data with intrinsic non-Euclidean structure. While Riemannian representation learning offers a solution by embedding data onto matching manifolds, it typically relies on an encoder to estimate densities on chosen manifolds. This involves optimizing numerically brittle objectives, potentially harming model