Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification. - Fenyu Hu; Yanqiao Zhu 001; Shu Wu; Liang Wang 001; Tieniu Tan (IJCAI, 2019)

Semi-supervised Node Classification via Hierarchical Graph Convolutional Networks. - Fenyu Hu; Yanqiao Zhu 001; Shu Wu; Liang Wang 001; Tieniu Tan (CoRR, 2019)

Fully Hyperbolic Graph Convolution Network for Recommendation. - Liping Wang; Fenyu Hu; Shu Wu; Liang Wang 001 (CIKM, 2021)

Label-informed Graph Structure Learning for Node Classification. - Liping Wang; Fenyu Hu; Shu Wu; Liang Wang 001 (CIKM, 2021)

Graph Classification by Mixture of Diverse Experts. - Fenyu Hu; Liping Wang; Shu Wu; Liang Wang 001; Tieniu Tan (CoRR, 2021)

GraphAIR: Graph representation learning with neighborhood aggregation and interaction. - Fenyu Hu; Yanqiao Zhu 001; Shu Wu; Weiran Huang 002; Liang Wang 001; Tieniu Tan (Pattern Recognit., 2021)

Second-Order Global Attention Networks for Graph Classification and Regression. - Fenyu Hu; Zeyu Cui; Shu Wu; Qiang Liu 006; Jinlin Wu; Liang Wang 001; Tieniu Tan (CICAI (2), 2022)

GraphDIVE: Graph Classification by Mixture of Diverse Experts. - Fenyu Hu; Liping Wang; Qiang Liu 006; Shu Wu; Liang Wang 001; Tieniu Tan (IJCAI, 2022)

Improving Multi-task GNNs for Molecular Property Prediction via Missing Label Imputation. - Fenyu Hu; Dingshuo Chen; Qiang Liu 006; Shu Wu (Mach. Intell. Res., 2025)