collaborators

5 papers

math.OC2026

Gromov-Wasserstein Barycenters: The Analysis Problem

Rocío Díaz Martín, Ivan V. Medri, James M. Murphy

This paper considers the problem of estimating a matrix that encodes pairwise distances in a finite metric space (or, more generally, the edge weight matrix of a network) under the…

stat.ML2026

Static and Dynamic Approaches to Computing Barycenters of Probability Measures on Graphs

David Gentile, James M. Murphy

The optimal transportation problem defines a geometry of probability measures which leads to a definition for weighted averages (barycenters) of measures, finding application in th…

math.ST2026

Wasserstein-based identification of metastable states in time series data via change point detection and segment clustering

David Gentile, Joshua Huang, James M. Murphy

Change point detection for time series analysis is a difficult and important problem in applied statistics, for which a variety of approaches have been developed in the past severa…

stat.ML2025

Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and Applications

Matthew Werenski, Brendan Mallery, Shuchin Aeron +1

We propose the linear barycentric coding model (LBCM) which utilizes the linear optimal transport (LOT) metric for analysis and synthesis of probability measures. We provide a clos…

stat.ML2025

Synthesis and Analysis of Data as Probability Measures with Entropy-Regularized Optimal Transport

Brendan Mallery, James M. Murphy, Shuchin Aeron

We consider synthesis and analysis of probability measures using the entropy-regularized Wasserstein-2 cost and its unbiased version, the Sinkhorn divergence. The synthesis problem…