Publisher
Springer Nature Singapore
Reference16 articles.
1. Agueh, M., Carlier, G.: Barycenters in the wasserstein space. SIAM J. Math. Anal. 43(2), 904–924 (2004)
2. Peyré, G., Cuturi, M.: Computational optimal transport, foundations and trends in machine. Learning 11(5–6), 355–607 (2019)
3. Srivastava, S., Li, C., Dunson, D.B.: Scalable Bayes via barycenter in Wasserstein space. J. Mach. Learn. Res. 19(8), 35 (2018)
4. Carlier, G., Oberman, A., Oudet, E.: Numerical methods for matching for teams and Wasserstein barycenters. ESAIM Math. Model. Numer. Anal. 49(6), 1621–1642 (2015)
5. Rabin, J., Peyré, G., Delon, J., Bernot, M.: Wasserstein Barycenter and its application to texture mixing. In: Lecture Notes in Computer Science, vol. 6667, Springer, Berlin, (2012), pp 435–446