Zhengyang Mao

According to our database, Zhengyang Mao authored at least 8 papers between 2023 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Self-supervised Graph-level Representation Learning with Adversarial Contrastive Learning.

Xiao Luo, Wei Ju, Yiyang Gu, Zhengyang Mao, Luchen Liu, Yuhui Yuan, Ming Zhang

ACM Trans. Knowl. Discov. Data, February, 2024

A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges.

Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S. Yu, Ming Zhang

CoRR, 2024

GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling.

Wei Ju, Yiyang Gu, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Xiao Luo, Hui Xiong, Ming Zhang

CoRR, 2024

A Survey on Graph Neural Networks in Intelligent Transportation Systems.

Hourun Li, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Zhiping Xiao, Jiaqi Feng, Yiyang Gu, Wei Ju, Xiao Luo, Ming Zhang

CoRR, 2024

2023

Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts.

Siyu Yi, Zhengyang Mao, Wei Ju, Yong-Dao Zhou, Luchen Liu, Xiao Luo, Ming Zhang

IEEE Trans. Big Data, December, 2023

Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts.

Siyu Yi, Zhengyang Mao, Wei Ju, Yongdao Zhou, Luchen Liu, Xiao Luo, Ming Zhang

CoRR, 2023

ALEX: Towards Effective Graph Transfer Learning with Noisy Labels.

Jingyang Yuan, Xiao Luo, Yifang Qin, Zhengyang Mao, Wei Ju, Ming Zhang

Proceedings of the 31st ACM International Conference on Multimedia, 2023

RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification.

Zhengyang Mao, Wei Ju, Yifang Qin, Xiao Luo, Ming Zhang

Proceedings of the 31st ACM International Conference on Multimedia, 2023