An Experimental Study of Class Imbalance in Federated Learning. - Chenguang Xiao; Shuo Wang 005 (SSCI, 2021)

FcTC-UNet: Fine-grained Combination of Transformer and CNN for Thoracic Organs Segmentation. - Liang Qiao; Qiang Liu; Jun Shi 007; Minfan Zhao; Hongyu Kan; Zhaohui Wang 002; Hong An; Chenguang Xiao; Shuo Wang 005 (EMBC, 2022)

Triplets Oversampling for Class Imbalanced Federated Datasets. - Chenguang Xiao; Shuo Wang 005 (ECML/PKDD (2), 2023)

Rethinking the initialization of Momentum in Federated Learning with Heterogeneous Data. - Chenguang Xiao; Shuo Wang (CoRR, 2024)

FedGA: Federated Learning with Gradient Alignment for Error Asymmetry Mitigation. - Chenguang Xiao; Zheming Zuo; Shuo Wang (CoRR, 2024)

Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes. - Zhaoyang Wang; Shuo Wang 005; Damien Ernst; Chenguang Xiao (IEEE Access, 2025)

Meta-Learning Enables Complex Cluster-Specific Few-Shot Binding Affinity Prediction for Protein-Protein Interactions. - Yang Yue; Yihua Cheng; Céline Marquet; Chenguang Xiao; Jingjing Guo; Shu Li; Shan He (J. Chem. Inf. Model., 2025)

Benchmarking Federated Machine Unlearning methods for Tabular Data. - Chenguang Xiao; Abhirup Ghosh; Han Wu; Shuo Wang; Diederick van Thiel (CoRR, 2025)