Bayesian uncertainty matching aligns joint feature-label distributions to improve unsupervised domain adaptation and reduce negative transfer on benchmark datasets.
What uncertainties do we need in bayesian deep learning for computer vision? In Advances in neural information processing systems , pages 5574--5584
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Bayesian Uncertainty Matching for Unsupervised Domain Adaptation
Bayesian uncertainty matching aligns joint feature-label distributions to improve unsupervised domain adaptation and reduce negative transfer on benchmark datasets.