37 citations · 108 across the 15 of their papers we have counts for
23 papers
Fermat Distances: Metric Approximation, Spectral Convergence, and Clustering Algorithms
Nicolás García Trillos, Anna Little, Daniel McKenzie +1
We analyze the convergence properties of Fermat distances, a family of density-driven metrics defined on Riemannian manifolds with an associated probability measure. Fermat distanc…
On Rank Energy Statistics via Optimal Transport: Continuity, Convergence, and Change Point Detection
Matthew Werenski, Shoaib Bin Masud, James M. Murphy +1
This paper considers the use of recently proposed optimal transport-based multivariate test statistics, namely rank energy and its variant the soft rank energy derived from entropi…
Geometric Sparse Coding in Wasserstein Space
Marshall Mueller, Shuchin Aeron, James M. Murphy +1
Wasserstein dictionary learning is an unsupervised approach to learning a collection of probability distributions that generate observed distributions as Wasserstein barycentric co…
Unsupervised Spatial-spectral Hyperspectral Image Reconstruction and Clustering with Diffusion Geometry
Kangning Cui, Ruoning Li, Sam L. Polk +3
Hyperspectral images, which store a hundred or more spectral bands of reflectance, have become an important data source in natural and social sciences. Hyperspectral images are oft…
Active Diffusion and VCA-Assisted Image Segmentation of Hyperspectral Images
Sam L. Polk, Kangning Cui, Robert J. Plemmons +1
Hyperspectral images encode rich structure that can be exploited for material discrimination by machine learning algorithms. This article introduces the Active Diffusion and VCA-As…
Measure Estimation in the Barycentric Coding Model
Matthew Werenski, Ruijie Jiang, Abiy Tasissa +2
This paper considers the problem of measure estimation under the barycentric coding model (BCM), in which an unknown measure is assumed to belong to the set of Wasserstein-2 baryce…