Search Results for author:
Found 1 papers, 0 papers with code
Principal subbundles for dimension reduction
In this paper we demonstrate how sub-Riemannian geometry can be used for manifold learning and surface reconstruction by combining local linear approximations of a point cloud to obtain lower dimensional bundles.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
