CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks. - Haotian Xue 001; Kaixiong Zhou; Tianlong Chen 001; Kai Guo 003; Xia Hu 001; Yi Chang 001; Xin Wang 035 (CoRR, 2021)

AutoAUG : Automatic Data Augmentation for Graph Neural Networks. - Xiao Liang; Xin Wang 035; Haotian Xue 001; Yintao Yang; Xin Juan; Ying Wang 009 (ACAI, 2022)

Adversarial Training on Weights for Graph Neural Networks. - Haotian Xue 001; Xin Wang 035; Ying Wang 009 (ACAI, 2022)

Negative samples selecting strategy for graph contrastive learning. - Rui Miao 003; Yintao Yang; Yao Ma 001; Xin Juan; Haotian Xue 001; Jiliang Tang; Ying Wang 009; Xin Wang 035 (Inf. Sci., 2022)

Multi-strategy adaptive data augmentation for Graph Neural Networks. - Xin Juan; Xiao Liang; Haotian Xue 001; Xin Wang 035 (Expert Syst. Appl., 2024)

A two-stage co-adversarial perturbation to mitigate out-of-distribution generalization of large-scale graph. - Yili Wang 004; Haotian Xue 001; Xin Wang 035 (Expert Syst. Appl., 2024)