12 citations · 20 across the 6 of their papers we have counts for
6 papers
Learning to Describe for Predicting Zero-shot Drug-Drug Interactions
Fangqi Zhu, Yongqi Zhang, Lei Chen +2
Adverse drug-drug interactions~(DDIs) can compromise the effectiveness of concurrent drug administration, posing a significant challenge in healthcare. As the development of new dr…
Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network
Yongqi Zhang, Quanming Yao, Ling Yue +4
Accurately predicting drug-drug interactions (DDI) for emerging drugs, which offer possibilities for treating and alleviating diseases, with computational methods can improve patie…
Positive-Unlabeled Node Classification with Structure-aware Graph Learning
Hansi Yang, Yongqi Zhang, Quanming Yao +1
Node classification on graphs is an important research problem with many applications. Real-world graph data sets may not be balanced and accurate as assumed by most existing works…
Relation-aware Ensemble Learning for Knowledge Graph Embedding
Ling Yue, Yongqi Zhang, Quanming Yao +5
Knowledge graph (KG) embedding is a fundamental task in natural language processing, and various methods have been proposed to explore semantic patterns in distinctive ways. In thi…
osmAG: Hierarchical Semantic Topometric Area Graph Maps in the OSM Format for Mobile Robotics
Delin Feng, Chengqian Li, Yongqi Zhang +2
Maps are essential to mobile robotics tasks like localization and planning. We propose the open street map (osm) XML based Area Graph file format to store hierarchical, topometric…
AutoWeird: Weird Translational Scoring Function Identified by Random Search
Hansi Yang, Yongqi Zhang, Quanming Yao
Scoring function (SF) measures the plausibility of triplets in knowledge graphs. Different scoring functions can lead to huge differences in link prediction performances on differe…