1 citations · 3 across the 5 of their papers we have counts for
4 papers · 1 filter
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…
A Multiscale Environment for Learning by Diffusion
James M. Murphy, Sam L. Polk
Clustering algorithms partition a dataset into groups of similar points. The clustering problem is very general, and different partitions of the same dataset could be considered co…
Spatially regularized active diffusion learning for high-dimensional images
James M. Murphy
An active learning algorithm for the classification of high-dimensional images is proposed in which spatially-regularized nonlinear diffusion geometry is used to characterize clust…
Learning by Active Nonlinear Diffusion
Mauro Maggioni, James M. Murphy
This article proposes an active learning method for high dimensional data, based on intrinsic data geometries learned through diffusion processes on graphs. Diffusion distances are…