Web: http://arxiv.org/abs/2106.05658

Jan. 31, 2022, 2:11 a.m. | Tianlin Xu, Beatrice Acciaio

cs.LG updates on arXiv.org arxiv.org

Causal Optimal Transport (COT) results from imposing a temporal causality
constraint on classic optimal transport problems, which naturally generates a
new concept of distances between distributions on path spaces. The first
application of the COT theory for sequential learning was given in Xu et al.
(2020), where COT-GAN was introduced as an adversarial algorithm to train
implicit generative models optimized for producing sequential data. Relying on
(Xu et al., 2020), the contribution of the present paper is twofold. First, we …

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