| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 8905727 | Comptes Rendus Mathematique | 2017 | 7 Pages |
Abstract
The notion of Wasserstein barycenters is a natural way to interpolate between several probability measures, useful in various applied settings like image processing or machine learning. We conjecture that such barycenters obey a central limit theorem which we prove in some (very) particular cases.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematics (General)
Authors
Martial Agueh, Guillaume Carlier,