The geometric median is a classic robust estimator of centrality for data in Euclidean spaces. In this paper we formulate the geometric median of data on a Riemannian manifold as ...
P. Thomas Fletcher, Suresh Venkatasubramanian, Sar...
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
Abstract. We investigate new approaches to quantifying the white matter connectivity in the brain using Diffusion Tensor Magnetic Resonance Imaging data. Our first approach finds a...
Lauren O'Donnell, Steven Haker, Carl-Fredrik Westi...
A convenient way of analysing Riemannian manifolds is to embed them in Euclidean spaces, with the embedding typically obtained by flattening the manifold via tangent spaces. This...
In the context of mesh adaptation, Riemannian metric spaces have been used to prescribe orientation, density and stretching of anisotropic meshes. But, such structures are only con...