Scalable unbalanced optimal transport using generative adversarial networks

Generative adversarial networks (GANs) are an expressive class of neural generative models with tremendous success in modeling high-dimensional continuous measures. In this paper, we present a scalable method for unbalanced optimal transport (OT) based on the generative-adversarial framework. We for...

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Bibliographic Details
Main Authors: Yang, Karren Dai (Author), Uhler, Caroline (Author)
Other Authors: Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: 2021-03-11T21:14:01Z.
Subjects:
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