One-Sided Unsupervised Domain Mapping

NeurIPS 2017 Sagie BenaimLior Wolf

In unsupervised domain mapping, the learner is given two unmatched datasets $A$ and $B$. The goal is to learn a mapping $G_{AB}$ that translates a sample in $A$ to the analog sample in $B$... (read more)

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