AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows
arXiv: Learning, 2019.
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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