AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows

national conference on artificial intelligence, 2020.

Cited by: 1|Bibtex|Views20|Links

Abstract:

Given unpaired data from multiple domains, a key challenge is to efficiently exploit these data sources for modeling a target domain. Variants of this problem have been studied in many contexts, such as cross-domain translation and domain adaptation. We propose AlignFlow, a generative modeling framework for learning from multiple domain...More

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