An Embedded Feature Selection Framework for Control. - Jiawen Wei 002; Fangyuan Wang 002; Wanxin Zeng; Wenwei Lin; Ning Gui (KDD, 2022)

Revisiting the robustness of post-hoc interpretability methods. - Jiawen Wei 002; Hugues Turbé; Gianmarco Mengaldo (CoRR, 2024)

Understanding via Exploration: Discovery of Interpretable Features With Deep Reinforcement Learning. - Jiawen Wei 002; Zhifeng Qiu; Fangyuan Wang 002; Wenwei Lin; Ning Gui; Weihua Gui 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

XAI4Extremes: An interpretable machine learning framework for understanding extreme-weather precursors under climate change. - Jiawen Wei 002; Aniruddha Bora; Vivek Oommen; Chenyu Dong; Juntao Yang; Jeff Adie; Chen Chen; Simon See; George E. Karniadakis; Gianmarco Mengaldo (CoRR, 2025)