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...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Published: |
2021
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| Online Access: | https://hdl.handle.net/1721.1/130122 |