C-ECAFormer: A new lightweight fault diagnosis framework towards heavy noise and small samples. - Jie Wang 160; Haidong Shao; Shen Yan 001; Bin Liu 025 (Eng. Appl. Artif. Intell., 2023)

SFDA-T: A novel source-free domain adaptation method with strong generalization ability for fault diagnosis. - Jie Wang 160; Haidong Shao; Yiming Xiao; Bin Liu 025 (Adv. Eng. Informatics, 2024)

Utilizing Bayesian generalization network for reliable fault diagnosis of machinery with limited data. - Minjie Feng; Haidong Shao; Minghui Shao; Yiming Xiao; Jie Wang 160; Bin Liu 025 (Knowl. Based Syst., 2024)

LiConvFormer: A lightweight fault diagnosis framework using separable multiscale convolution and broadcast self-attention. - Shen Yan 001; Haidong Shao; Jie Wang 160; Xinyu Zheng; Bin Liu 025 (Expert Syst. Appl., 2024)

PSparseFormer: Enhancing Fault Feature Extraction Based on Parallel Sparse Self-Attention and Multiscale Broadcast Feedforward Block. - Jie Wang 160; Haidong Shao; Ying Peng; Bin Liu 025 (IEEE Internet Things J., 2024)

Domain generalization for rotating machinery fault diagnosis: A survey. - Yiming Xiao; Haidong Shao; Shen Yan 001; Jie Wang 160; Ying Peng; Bin Liu 025 (Adv. Eng. Informatics, 2025)

Domain-augmented meta ensemble learning for mechanical fault diagnosis from heterogeneous source domains to unseen target domains. - Yiming Xiao; Haidong Shao; Jie Wang 160; Baoping Cai; Bin Liu 025 (Expert Syst. Appl., 2025)

From deterministic to Bayesian: Adapting pre-trained models for human-computer collaborative fault diagnosis via post-hoc uncertainty. - Yiming Xiao; Haidong Shao; Jie Wang 160; Baoping Cai; Bin Liu 025 (J. Ind. Inf. Integr., 2025)

A novel interpretable fault diagnosis method using multi-image feature extraction and attention fusion. - Jie Wang 160; Haidong Shao; Jing He; Le Liu; Jingqiang Ma; Bin Liu 025 (Pattern Recognit. Lett., 2025)