2025

• Learning from Graph-Graph Relationship A New Perspective On Graph-level Anomaly Detection
  Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Hao Peng, Pietro Liò
  TKDE (IF 10.4, CCF-A)

• Enhancing Graph Neural Networks for Out-of-distribution Graph Detection
  Ge Zhang, Zhenyu Yang, Jia Wu, Pengfei Jiao, Jian Yang
  TNNLS (IF 8.9, CCF-B)

• 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
  SIGKDD (CORE A*, CCF-A)

2024

• 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 Hancock, Pietro Li`o
  CSUR (IF 28)

• 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
  WSDM (CORE A, CCF-B)

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
  NeurIPS (CORE A*, CCF-A)

• Low-rank and Sparse Representation Based Learning for Cancer Survivability Prediction
  Jie Yang, Jun Ma, Khin Than Win, Junbin Gao, Zhenyu Yang
  Information Science (CCF-B)