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Sample Complexity of Sinkhorn Divergences, , , , и . Proceedings of Machine Learning Research, том 89 из Proceedings of Machine Learning Research, стр. 1574--1583. PMLR, (16--18 Apr 2019)Stochastic Deep Networks, , и . (2018)cite arxiv:1811.07429.Learning Generative Models with Sinkhorn Divergences., , и . AISTATS, том 84 из Proceedings of Machine Learning Research, стр. 1608-1617. PMLR, (2018)Ground metric learning., и . J. Mach. Learn. Res., 15 (1): 533-564 (2014)Geodesic PCA versus Log-PCA of Histograms in the Wasserstein Space., , , , и . SIAM J. Sci. Comput., (2018)Mean Reversion with a Variance Threshold., и . ICML (3), том 28 из JMLR Workshop and Conference Proceedings, стр. 271-279. JMLR.org, (2013)Fast Computation of Wasserstein Barycenters., и . ICML, том 32 из JMLR Workshop and Conference Proceedings, стр. 685-693. JMLR.org, (2014)Wasserstein regularization for sparse multi-task regression., , и . AISTATS, том 89 из Proceedings of Machine Learning Research, стр. 1407-1416. PMLR, (2019)Differentiable Sorting using Optimal Transport: The Sinkhorn CDF and Quantile Operator., , и . CoRR, (2019)Multi-subject MEG/EEG source imaging with sparse multi-task regression., , , , и . CoRR, (2019)