Graph Mask Convolutional Network. - Bo Jiang 002; Beibei Wang 006; Jin Tang 001; Bin Luo 001 (CoRR, 2019)

Generalizing Aggregation Functions in GNNs: High-Capacity GNNs via Nonlinear Neighborhood Aggregators. - Beibei Wang 006; Bo Jiang 002 (CoRR, 2022)

Spiking GATs: Learning Graph Attentions via Spiking Neural Network. - Beibei Wang 006; Bo Jiang 002 (CoRR, 2022)

MGLNN: Semi-supervised learning via Multiple Graph Cooperative Learning Neural Networks. - Bo Jiang 002; Si Chen; Beibei Wang 006; Bin Luo 001 (Neural Networks, 2022)

GeCNs: Graph Elastic Convolutional Networks for Data Representation. - Bo Jiang 002; Beibei Wang 006; Jin Tang 001; Bin Luo 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

DropAGG: Robust Graph Neural Networks via Drop Aggregation. - Bo Jiang 002; Yong Chen; Beibei Wang 006; Haiyun Xu; Bin Luo 001 (Neural Networks, 2023)

Data Representation via Attribute Selection- Propagation Neural Network. - Beibei Wang 006; Bo Jiang 002 (IEEE Trans. Signal Inf. Process. over Networks, 2023)

Sparse norm regularized attribute selection for graph neural networks. - Bo Jiang 002; Beibei Wang 006; Bin Luo 001 (Pattern Recognit., 2023)

Graph Neural Network Meets Sparse Representation: Graph Sparse Neural Networks via Exclusive Group Lasso. - Bo Jiang 002; Beibei Wang 006; Si Chen; Jin Tang 001; Bin Luo 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Generalizing Aggregation Functions in GNNs: Building High Capacity and Robust GNNs via Nonlinear Aggregation. - Beibei Wang 006; Bo Jiang 002; Jin Tang 001; Bin Luo 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

A Unified Graph Selective Prompt Learning for Graph Neural Networks. - Bo Jiang 002; Hao Wu; Ziyan Zhang; Beibei Wang 006; Jin Tang 001 (CoRR, 2024)

Graph Edge Representation via Tensor Product Graph Convolutional Representation. - Bo Jiang 002; Sheng Ge; Ziyan Zhang; Beibei Wang 006; Jin Tang 001; Bin Luo 001 (CoRR, 2024)

Reliable and Compact Graph Fine-tuning via GraphSparse Prompting. - Bo Jiang 002; Hao Wu; Beibei Wang 006; Jin Tang 001; Bin Luo 001 (CoRR, 2024)

FL-GNNs: Robust Network Representation via Feature Learning Guided Graph Neural Networks. - Beibei Wang 006; Bo Jiang 002; Chris Ding (IEEE Trans. Netw. Sci. Eng., 2024)

GDCNet: Graph Enrichment Learning via Graph Dropping Convolutional Networks. - Bo Jiang 002; Yong Chen; Beibei Wang 006; Haiyun Xu; Jin Tang 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Learning Graph Attentions via Replicator Dynamics. - Bo Jiang 002; Ziyan Zhang; Sheng Ge; Beibei Wang 006; Xiao Wang 014; Jin Tang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

UGG-ReID: Uncertainty-Guided Graph Model for Multi-Modal Object Re-Identification. - Xixi Wan; Aihua Zheng; Bo Jiang 002; Beibei Wang 006; Chenglong Li 002; Jin Tang 001 (CoRR, 2025)

Beyond Graph Model: Reliable VLM Fine-Tuning via Random Graph Adapter. - Bo Jiang 002; Xueyang Ze; Beibei Wang 006; Xixi Wang; Xixi Wan; Bin Luo 001 (CoRR, 2025)

Graph Spiking Attention Network: Sparsity, Efficiency and Robustness. - Beibei Wang 006; Bo Jiang 002; Jin Tang 001; Lu Bai 001; Bin Luo 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)