Feature Selection for Fault Detection and Prediction based on Event Log Analysis. - Zhong Li 002; Matthijs van Leeuwen (SIGKDD Explor., 2022)

Robust and Explainable Contextual Anomaly Detection using Quantile Regression Forests. - Zhong Li 002; Matthijs van Leeuwen (CoRR, 2023)

Graph Neural Network based Log Anomaly Detection and Explanation. - Zhong Li 002; Jiayang Shi; Matthijs van Leeuwen (CoRR, 2023)

Explainable contextual anomaly detection using quantile regression forests. - Zhong Li 002; Matthijs van Leeuwen (Data Min. Knowl. Discov., 2023)

Graph Neural Networks based Log Anomaly Detection and Explanation. - Zhong Li 002; Jiayang Shi; Matthijs van Leeuwen (ICSE Companion, 2024)

Explainable Graph Neural Networks Under Fire. - Zhong Li 002; Simon Geisler; Yuhang Wang; Stephan Günnemann; Matthijs van Leeuwen (CoRR, 2024)

A Survey on Explainable Anomaly Detection. - Zhong Li 002; Yuxuan Zhu; Matthijs van Leeuwen (ACM Trans. Knowl. Discov. Data, 2024)

Cross-Domain Graph Level Anomaly Detection. - Zhong Li 002; Sheng Liang; Jiayang Shi; Matthijs van Leeuwen (IEEE Trans. Knowl. Data Eng., 2024)

Diffusion Models for Tabular Data: Challenges, Current Progress, and Future Directions. - Zhong Li 002; Qi Huang; Lincen Yang; Jiayang Shi; Zhao Yang; Niki van Stein; Thomas Bäck; Matthijs van Leeuwen (CoRR, 2025)

Towards automated self-supervised learning for truly unsupervised graph anomaly detection. - Zhong Li 002; Yuhang Wang; Matthijs van Leeuwen (Data Min. Knowl. Discov., 2025)