Bayesian Quadrature on Riemannian Data Manifolds
Christian Frohlich 1 Alexandra Gessner * 1 2 Philipp Hennig 1 2 Bernhard Scholkopf 2 Georgios Arvanitidis * 2
Abstract
Riemannian manifolds provide a principled way
to model nonlinear geometric structure inherent
in data. A Riemannian metric on said manifolds
determines geometry-aware shortest paths and
provides the means to define statistical models ac-
cordingly. However, these operations are typically
comp ...


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