Zhengyang Mao

According to our database, Zhengyang Mao authored at least 22 papers between 2023 and 2026.

Collaborative distances:

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

2026

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, Philip S. Yu, Ming Zhang

IEEE Trans. Pattern Anal. Mach. Intell., March, 2026

Identifying and Correcting Label Noise for Robust GNNs via Influence Contradiction.

Wei Ju, Wei Zhang, Siyu Yi, Zhengyang Mao, Yifan Wang, Jingyang Yuan, Zhiping Xiao, Ziyue Qiao, Ming Zhang

CoRR, January, 2026

DEER: Distribution Divergence-Based Graph Contrast for Partial Label Learning on Graphs.

Yiyang Gu, Zihao Chen, Yifang Qin, Zhengyang Mao, Zhiping Xiao, Wei Ju, Chong Chen, Xian-Sheng Hua, Yifan Wang, Xiao Luo, Ming Zhang

IEEE Trans. Multim., 2026

Long-Tailed Recognition of Evidential Experts for Graph-level Classification.

Wei Ju, Siyu Yi, Zhengyang Mao, Yifang Qin, Yifan Wang, Zhiping Xiao, Yiwei Fu, Ziyue Qiao, Ming Zhang

Proceedings of the ACM Web Conference 2026, 2026

2025

AlphaEval: A Comprehensive and Efficient Evaluation Framework for Formula Alpha Mining.

Hongjun Ding, Binqi Chen, Jinsheng Huang, Taian Guo, Zhengyang Mao, Guoyi Shao, Lutong Zou, Luchen Liu, Ming Zhang

CoRR, August, 2025

MASS: Multi-Agent Simulation Scaling for Portfolio Construction.

Taian Guo, Haiyang Shen, Jinsheng Huang, Zhengyang Mao, Junyu Luo, Zhuoru Chen, Xuhui Liu, Bingyu Xia, Luchen Liu, Yun Ma, Ming Zhang

CoRR, May, 2025

Learning Knowledge-diverse Experts for Long-tailed Graph Classification.

Zhengyang Mao, Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Qingqing Long, Nan Yin, Xinwang Liu, Ming Zhang

ACM Trans. Knowl. Discov. Data, February, 2025

Learning Generalizable Contrastive Representations for Graph Zero-Shot Learning.

Siyu Yi, Zhengyang Mao, Kangjie Zheng, Zhiping Xiao, Ziyue Qiao, Chong Chen, Xian-Sheng Hua, Yong-Dao Zhou, Ming Zhang, Wei Ju

IEEE Trans. Multim., 2025

Hypergraph Consistency Learning With Relational Distillation.

Siyu Yi, Zhengyang Mao, Yifan Wang, Yiyang Gu, Zhiping Xiao, Chong Chen, Xian-Sheng Hua, Ming Zhang, Wei Ju

IEEE Trans. Multim., 2025

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

Sci. China Inf. Sci., 2025

Cluster-guided Contrastive Class-imbalanced Graph Classification.

Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Jianhao Shen, Ziyue Qiao, Ming Zhang

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

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

Focus on informative graphs! Semi-supervised active learning for graph-level classification.

Wei Ju, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Siyu Yi, Zhiping Xiao, Xiao Luo, Yanjie Fu, Ming Zhang

Pattern Recognit., 2024

Towards Graph Contrastive Learning: A Survey and Beyond.

Wei Ju, Yifan Wang, Yifang Qin, Zhengyang Mao, Zhiping Xiao, Junyu Luo, Junwei Yang, Yiyang Gu, Dongjie Wang, Qingqing Long, Siyu Yi, Xiao Luo, Ming Zhang

CoRR, 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

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

Hypergraph-enhanced Dual Semi-supervised Graph Classification.

Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Yifan Wang, Xiao Luo, Ming Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 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

Zero-shot Node Classification with Graph Contrastive Embedding Network.

Wei Ju, Yifang Qin, Siyu Yi, Zhengyang Mao, Kangjie Zheng, Luchen Liu, Xiao Luo, Ming Zhang

Trans. Mach. Learn. Res., 2023

RIGNN: A Rationale Perspective for Semi-supervised Open-world Graph Classification.

Xiao Luo, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun

Trans. Mach. Learn. Res., 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