Generalized Wasserstein Barycenters

Abstract We study the existence and uniqueness of the barycenter of a signed distribution of probability measures on a Hilbert space. The barycenter is found, as usual, as a minimum of a functional. In the case where the positive part of the signed measure is a singleton, we can show also uniqueness. In the one-dimensional case, we characterize the quantile function of the unique minimum as the orthogonal projection of the $$L^2$$ -barycenter of the quantiles on the cone of nonincreasing functions in $$L^2(0,1)$$ . Further, we provide a stability estimate in dimension one and a counterexample to uniqueness in $$\mathbb {R}^2$$ . Finally, we address the consistency of the barycenters and we prove that barycenters of a sequence of approximating measures converge (up to subsequences) to a barycenter of the limit measure.

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Publication Details

Journal
Applied Mathematics & Optimization
Published
2025-11-07
DOI
https://doi.org/10.1007/s00245-025-10351-6
Primary Topic
Geometric Analysis and Curvature Flows
Type
article
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article

Generalized Wasserstein Barycenters

Marco Veneroni, Giuseppe Savaré, Francesco Tornabene
Applied Mathematics & Optimization
Geometric Analysis and Curvature Flows
article

Generalized Wasserstein Barycenters

Marco Veneroni, Giuseppe Savaré, Francesco Tornabene
article en

Abstract

Abstract We study the existence and uniqueness of the barycenter of a signed distribution of probability measures on a Hilbert space. The barycenter is found, as usual, as a minimum of a functional. In the case where the positive part of the signed measure is a singleton, we can show also uniqueness. In the one-dimensional case, we characterize the quantile function of the unique minimum as the orthogonal projection of the $$L^2$$ -barycenter of the quantiles on the cone of nonincreasing functions in $$L^2(0,1)$$ . Further, we provide a stability estimate in dimension one and a counterexample to uniqueness in $$\mathbb {R}^2$$ . Finally, we address the consistency of the barycenters and we prove that barycenters of a sequence of approximating measures converge (up to subsequences) to a barycenter of the limit measure.

Applied Mathematics & OptimizationVol. 92(3)
University of Pavia (IT), Gran Sasso Science Institute (IT), Bocconi University (IT)
Openalex Percentile: Top 54%
Geometric Analysis and Curvature Flows
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