Publications (4)
An open unified deep graph learning framework for discovering drug leads
Yueming Yin, Haifeng Hu, Zhen Yang +4
Computational discovery of ideal lead compounds is a critical process for modern drug discovery. It comprises multiple stages: hit screening, molecular property prediction, and mol…
Universal Multi-Source Domain Adaptation
Yueming Yin, Zhen Yang, Haifeng Hu +1
Unsupervised domain adaptation enables intelligent models to transfer knowledge from a labeled source domain to a similar but unlabeled target domain. Recent study reveals that kno…
Unveiling Class-Labeling Structure for Universal Domain Adaptation
Yueming Yin, Zhen Yang, Xiaofu Wu +1
As a more practical setting for unsupervised domain adaptation, Universal Domain Adaptation (UDA) is recently introduced, where the target label set is unknown. One of the big chal…
Metric-Learning-Assisted Domain Adaptation
Yueming Yin, Zhen Yang, Haifeng Hu +1
Domain alignment (DA) has been widely used in unsupervised domain adaptation. Many existing DA methods assume that a low source risk, together with the alignment of distributions o…