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Published in Briefings in Bioinformatics, 2023
We present a general dynamic hypergraph contrastive learning framework for multi-relational DGI prediction, with remarkable effectiveness, robustness and generalization.
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Published in arXiv, 2023
We propose a Denoised Link Prediction framework to denoise unreliable interactions existing in the biomedical knowledge graph for link prediction.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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