We don’t have enough information about this author to calculate their statistics. If you think this is an error let us know.
Learn More
For inference on non-Euclidean data, ideally the data space is at least locally approx-<lb>imated by a Euclidean space; for a manifold by a chart, say. If suitable data descriptors<lb>lie asymptotically in such a common Euclidean neighborhood, one would expect a normal<lb>central limit theorem to hold. Already for locally flat spaces like the circle there(More)
  • 1