3 papers
cs.LG2026
Regional Explanations via Causal Sufficiency and Necessity
Xuexin Chen, Peng Liang, Zijian Li +2
Model explainability is essential for understanding and trusting machine learning models. Existing explainable AI methods often explain predictions through feature importance, coun…
cs.DB2025
Efficient Mining of Low-Utility Sequential Patterns
Jian Zhu, Zhidong Lin, Wensheng Gan +1
Discovering valuable insights from rich data is a crucial task for exploratory data analysis. Sequential pattern mining (SPM) has found widespread applications across various domai…
cs.LG2025
Interpretable High-order Knowledge Graph Neural Network for Predicting Synthetic Lethality in Human Cancers
Xuexin Chen, Ruichu Cai, Zhengting Huang +3
Synthetic lethality (SL) is a promising gene interaction for cancer therapy. Recent SL prediction methods integrate knowledge graphs (KGs) into graph neural networks (GNNs) and emp…