Image Guided Fuzzy C-Means for Image Segmentation. - Li Guo 016; Long Chen 001; Yingwen Wu; C. L. Philip Chen (Int. J. Fuzzy Syst., 2017)

Learn Robust Features via Orthogonal Multi-Path. - Kun Fang 004; Yingwen Wu; Tao Li; Xiaolin Huang; Jie Yang 002 (CoRR, 2020)

Subspace Adversarial Training. - Tao Li; Yingwen Wu; Sizhe Chen; Kun Fang 004; Xiaolin Huang (CVPR, 2022)

Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks. - Sizhe Chen; Zhehao Huang; Qinghua Tao; Yingwen Wu; Cihang Xie; Xiaolin Huang (NeurIPS, 2022)

Trainable Weight Averaging for Fast Convergence and Better Generalization. - Tao Li; Zhehao Huang; Qinghua Tao; Yingwen Wu; Xiaolin Huang (CoRR, 2022)

Efficient Generalization Improvement Guided by Random Weight Perturbation. - Tao Li; Weihao Yan; Zehao Lei; Yingwen Wu; Kun Fang 004; Ming Yang; Xiaolin Huang (CoRR, 2022)

Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions. - Tao Li; Zhehao Huang; Qinghua Tao; Yingwen Wu; Xiaolin Huang (ICLR, 2023)

Identifying firm-specific technology opportunities in a supply chain: Link prediction analysis in multilayer networks. - Yingwen Wu; Yangjian Ji; Fu Gu (Expert Syst. Appl., 2023)

Identifying firm-specific technology opportunities from the perspective of competitors by using association rule mining. - Yingwen Wu; Yangjian Ji (J. Informetrics, 2023)

Unifying Gradients to Improve Real-World Robustness for Deep Networks. - Yingwen Wu; Sizhe Chen; Kun Fang 004; Xiaolin Huang (ACM Trans. Intell. Syst. Technol., 2023)

Better Generalization in Fast Training: Flat Trainable Weight in Subspace. - Zehao Lei; Yingwen Wu; Tao Li (ICMLC, 2024)

Towards robust neural networks via orthogonal diversity. - Kun Fang 004; Qinghua Tao; Yingwen Wu; Tao Li; Jia Cai; Feipeng Cai; Xiaolin Huang; Jie Yang 002 (Pattern Recognit., 2024)

Online Continual Learning via Logit Adjusted Softmax. - Zhehao Huang; Tao Li; Chenhe Yuan; Yingwen Wu; Xiaolin Huang (Trans. Mach. Learn. Res., 2024)

Revisiting Random Weight Perturbation for Efficiently Improving Generalization. - Tao Li; Qinghua Tao; Weihao Yan; Yingwen Wu; Zehao Lei; Kun Fang 004; Mingzhen He; Xiaolin Huang (Trans. Mach. Learn. Res., 2024)

Low-Dimensional Gradient Helps Out-of-Distribution Detection. - Yingwen Wu; Tao Li; Xinwen Cheng; Jie Yang 002; Xiaolin Huang (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Toward Transferable Adversarial Attacks Against Autoencoder-Based Network Intrusion Detectors. - Yihang Zhang; Yingwen Wu; Xiaolin Huang (IEEE Trans. Ind. Informatics, 2024)

Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection. - Yingwen Wu; Ruiji Yu; Xinwen Cheng; Zhengbao He; Xiaolin Huang (ICLR, 2025)

Multi-head ensemble of smoothed classifiers for certified robustness. - Kun Fang 004; Qinghua Tao; Yingwen Wu; Tao Li; Xiaolin Huang; Jie Yang 002 (Neural Networks, 2025)