Zhenyu Yang

According to our database, Zhenyu Yang authored at least 15 papers between 2020 and 2026.

Collaborative distances:

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

2026

Adaptive graph search for multi-agent rescue operations in natural disaster response.

Qihua Lyu, Cao Xin, Yongsheng Yu, Shan Xue, Jian Yang, Zhenyu Yang, Amin Beheshti, Jia Wu

Int. J. Mach. Learn. Cybern., July, 2026

FedHPro: Federated Hyper-Prototype Learning via Gradient Matching.

Huan Wang, Jun Shen, Haoran Li, Zhenyu Yang, Jun Yan, Ousman Manjang, Yanlong Zhai, Di Wu, Guansong Pang

CoRR, May, 2026

Learning From Graph-Graph Relationship: A New Perspective on Graph-Level Anomaly Detection.

Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Hao Peng, Pietro Lió

IEEE Trans. Knowl. Data Eng., January, 2026

Learning Subgraph-Based Normality for Interpretable Graph-Level Anomaly Detection.

Ge Zhang, Zhenyu Yang, Jia Wu, Pengfei Jiao, Jian Yang, Hao Peng, Xixun Lin

IEEE Trans. Inf. Forensics Secur., 2026

Generalizable Graph-level Anomaly Detection via Prompted Anomaly Expansion and Normality Extraction.

Ge Zhang, Jiapei Chen, Guohao Sun, Xiu Fang, Zhenyu Yang, Xixun Lin, Liang Yang

Proceedings of the ACM Web Conference 2026, 2026

Revisiting Graph-Level Anomaly Detection: From Partially to Fully Unsupervised Learning.

Zhenyu Yang, Ge Zhang, Shan Xue, Xiaoxiao Ma, Jian Yang, Hao Peng, Amin Beheshti, Jia Wu

Proceedings of the ACM Web Conference 2026, 2026

Semi-Supervised Fake News Detection with Mixture of Experts.

Zhenyu Yang, Chaoyu Yang, Wenfeng Xu, Xiuxiu Hao, Huan Wang, Ge Zhang, Xiaoxiao Ma, Jun Shen

Proceedings of the ACM Web Conference 2026, 2026

2025

Enhancing Graph Neural Networks for Out-of-Distribution Graph Detection.

Ge Zhang, Zhenyu Yang, Jia Wu, Pengfei Jiao, Jian Yang

IEEE Trans. Neural Networks Learn. Syst., October, 2025

State of the Art and Potentialities of Graph-level Learning.

Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu Aggarwal, Hao Peng, Wenbin Hu, Edwin R. Hancock, Pietro Liò

ACM Comput. Surv., February, 2025

Global Interpretable Graph-level Anomaly Detection via Prototype.

Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Hao Peng, Quan Z. Sheng

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

2023

A Comprehensive Survey of Graph-level Learning.

Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu C. Aggarwal, Hao Peng, Wenbin Hu, Edwin R. Hancock, Pietro Liò

CoRR, 2023

Minimum Entropy Principle Guided Graph Neural Networks.

Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Hao Peng, Angsheng Li, Shan Xue, Jianlin Su

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

2022

Low-rank and sparse representation based learning for cancer survivability prediction.

Jie Yang, Jun Ma, Khin Than Win, Junbin Gao, Zhenyu Yang

Inf. Sci., 2022

Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection.

Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020

Multi-view learning for context-aware extractive summarization.

Zhenyu Yang, Jie Yang, Brian Yecies, Wanqing Li

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020