The increasing diversity of scientific and engineering data has driven the development of flexible techniques for inferring probability distributions without assuming a specific parametric family.
Nonparametric density estimation on Riemannian manifolds extends classical techniques to data that lie on curved spaces rather than in Euclidean domains. Such manifolds may arise as spheres, rotation ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results