Low Rank Self-calibrated Brain Network Estimation and Autoweighted Centralized Multi-Task Learning for Early Mild Cognitive Impairment Diagnosis. - Nina Cheng; Ahmed El-Azab; Peng Yang 011; Dongdong Liu; Shuangzhi Yu; Tianfu Wang 001; Baiying Lei (EMBC, 2019)

Multi-scale Graph Convolutional Network for Mild Cognitive Impairment Detection. - Shuangzhi Yu; Guanghui Yue 001; Ahmed Elazab; Xuegang Song; Tianfu Wang 001; Baiying Lei (GLMI@MICCAI, 2019)

Multi-scale Enhanced Graph Convolutional Network for Early Mild Cognitive Impairment Detection. - Shuangzhi Yu; Shuqiang Wang; Xiaohua Xiao; Jiuwen Cao; Guanghui Yue 001; Dongdong Liu; Tianfu Wang 001; Yanwu Xu 001; Baiying Lei (MICCAI (7), 2020)

Multi-channel Sparse Graph Transformer Network for Early Alzheimer's Disease Identification. - Yali Qiu; Shuangzhi Yu; Yanhong Zhou; Dongdong Liu; Xuegang Song; Tianfu Wang 001; Baiying Lei (ISBI, 2021)

Longitudinal study of early mild cognitive impairment via similarity-constrained group learning and self-attention based SBi-LSTM. - Baiying Lei; Yuwen Zhang; Dongdong Liu; Yanwu Xu 001; Guanghui Yue 001; Jiuwen Cao; Huoyou Hu; Shuangzhi Yu; Peng Yang 011; Tianfu Wang 001; Yali Qiu; Xiaohua Xiao; et al. (Knowl. Based Syst., 2022)

Multi-scale enhanced graph convolutional network for mild cognitive impairment detection. - Baiying Lei; Yun Zhu; Shuangzhi Yu; Huoyou Hu; Yanwu Xu 001; Guanghui Yue 001; Tianfu Wang 001; Cheng Zhao 003; Shaobin Chen; Peng Yang 011; Xuegang Song; Xiaohua Xiao; et al. (Pattern Recognit., 2023)

A traffic state prediction method based on spatial-temporal data mining of floating car data by using autoformer architecture. - Shuangzhi Yu; Jiankun Peng; Yuming Ge; Xinlian Yu; Fan Ding; Shen Li; Charlie Ma (Comput. Aided Civ. Infrastructure Eng., 2024)

UKD-TEAD: An Unsupervised Knowledge Distillation Framework for Detecting Anomalies in Traffic Equipment With Various Aspect Ratios. - Di Wu 071; Jiankun Peng; Shuangzhi Yu; Yuming Ge; Chunye Ma; Jiaxuan Zhou (IEEE Internet Things J., 2025)