Cross-attention-guided subject-adaptive graph learning for multimodal autism classification: integrating structural and functional MRI data. [PDF]
Brain InformTang Y, Yang C, Xu Y, Zhang H, Xie H.
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scHG: A supercell framework with high-order graph learning enables scalable multi-omics analysis. [PDF]
PLoS Comput BiolHuang Y, Gan Y, Gong X.
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Metapath2vec and attention-driven heterogeneous graph learning for prioritizing TCM-derived small molecules in gastric cancer. [PDF]
Chin MedSheng N +6 more
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Real-time dynamic graph learning with temporal attention for financial fraud detection. [PDF]
Front Artif IntellChen J, Yang Y.
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Graph Learning: A Survey [PDF]
IEEE Transactions on Artificial Intelligence, 2021 Graphs are widely used as a popular representation of the network structure of connected data. Graph data can be found in a broad spectrum of application domains such as social systems, ecosystems, biological networks, knowledge graphs, and information ...
Huan Liu, Feng Xia
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