Meta-GNN: On Few-shot Node Classification in Graph Meta-learning. - Fan Zhou 002; Chengtai Cao; Kunpeng Zhang 001; Goce Trajcevski; Ting Zhong; Ji Geng 001 (CIKM, 2019)

Fast Network Alignment via Graph Meta-Learning. - Fan Zhou 002; Chengtai Cao; Goce Trajcevski; Kunpeng Zhang 001; Ting Zhong; Ji Geng 001 (INFOCOM, 2020)

Continual Graph Learning. - Fan Zhou 002; Chengtai Cao; Ting Zhong; Kunpeng Zhang 001; Goce Trajcevski; Ji Geng 001 (CoRR, 2020)

Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay. - Fan Zhou 002; Chengtai Cao (AAAI, 2021)

Trajectory-User Linking via Graph Neural Network. - Fan Zhou 002; Shupei Chen; Jin Wu 002; Chengtai Cao; Shengming Zhang (ICC, 2021)

Learning meta-knowledge for few-shot image emotion recognition. - Fan Zhou 002; Chengtai Cao; Ting Zhong; Ji Geng 001 (Expert Syst. Appl., 2021)

A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability. - Chengtai Cao; Fan Zhou 002; Yurou Dai; Jianping Wang 001 (CoRR, 2022)

CCTR: Calibrating Trajectory Prediction for Uncertainty-Aware Motion Planning in Autonomous Driving. - Chengtai Cao; Xinhong Chen 003; Jianping Wang 001; Qun Song 001; Rui Tan 001; Yung-Hui Li (AAAI, 2024)

SGDCL: Semantic-Guided Dynamic Correlation Learning for Explainable Autonomous Driving. - Chengtai Cao; Xinhong Chen 003; Jianping Wang 001; Qun Song 001; Rui Tan 001; Yung-Hui Li (IJCAI, 2024)

Facing Anomalies Head-On: Network Traffic Anomaly Detection via Uncertainty-Inspired Inter-Sample Differences. - Xinglin Lian; Chengtai Cao; Yan Liu; Xovee Xu; Yu Zheng 006; Fan Zhou 002 (WWW, 2025)

A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability. - Chengtai Cao; Fan Zhou 002; Yurou Dai; Jianping Wang 001; Kunpeng Zhang 001 (ACM Comput. Surv., 2025)