Matthew Werenski — accepted AI-conference papers

2025

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

Matthew Werenski, Brendan Mallery, Shuchin Aeron, James M. Murphy

AISTATS 2025poster

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 closed-form solution to the variational problem characterizing the probability measures in the LBCM and establish equivalen…

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2022

Measure Estimation in the Barycentric Coding Model

Matthew Werenski, Ruijie Jiang, Abiy Tasissa, Shuchin Aeron, James M Murphy

ICML 2022spotlight

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 barycenters of a finite set of known measures. Estimating a measure under this model is equivalent to estimating the unknown b…

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