Ensemble Universum SVM Learning for Multimodal Classification of Alzheimer's Disease. - Xiaoke Hao; Daoqiang Zhang (MLMI, 2013)

Identifying Genetic Associations with MRI-derived Measures via Tree-Guided Sparse Learning. - Xiaoke Hao; Jintai Yu; Daoqiang Zhang (MICCAI (2), 2014)

Diagnosis-Guided Method for Identifying Multi-Modality Neuroimaging Biomarkers Associated with Genetic Risk Factors in Alzheimer's Disease. - Xiaoke Hao; Jingwen Yan; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Daoqiang Zhang; Li Shen 001 (PSB, 2016)

Identifying Multimodal Intermediate Phenotypes Between Genetic Risk Factors and Disease Status in Alzheimer's Disease. - Xiaoke Hao; Xiaohui Yao; Jingwen Yan; Shannon L. Risacher; Andrew J. Saykin; Daoqiang Zhang; Li Shen 001 (Neuroinformatics, 2016)

Multi-level Multi-task Structured Sparse Learning for Diagnosis of Schizophrenia Disease. - Mingliang Wang; Xiaoke Hao; Jiashuang Huang; Kangcheng Wang; Xijia Xu; Daoqiang Zhang (MICCAI (3), 2017)

Identification of associations between genotypes and longitudinal phenotypes via temporally-constrained group sparse canonical correlation analysis. - Xiaoke Hao; Chanxiu Li; Jingwen Yan; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Daoqiang Zhang (Bioinform., 2017)

Deep Regression Neural Network for End-to-End Person Re-Identification. - Yingchun Guo; Kunpeng Zhao; Xiaoke Hao; Ming Yu 006 (IEEE Access, 2019)

Discovering network phenotype between genetic risk factors and disease status via diagnosis-aligned multi-modality regression method in Alzheimer's disease. - Meiling Wang 001; Xiaoke Hao; Jiashuang Huang; Wei Shao 005; Daoqiang Zhang (Bioinform., 2019)

Multi-modal AD classification via self-paced latent correlation analysis. - Qi Zhu 001; Ning Yuan; Jiashuang Huang; Xiaoke Hao; Daoqiang Zhang (Neurocomputing, 2019)

Identifying Candidate Genetic Associations with MRI-Derived AD-Related ROI via Tree-Guided Sparse Learning. - Xiaoke Hao; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Jintai Yu; Huifu Wang; Lan Tan; Li Shen 001; Daoqiang Zhang (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Identifying Resting-State Multifrequency Biomarkers via Tree-Guided Group Sparse Learning for Schizophrenia Classification. - Jiashuang Huang; Qi Zhu 001; Xiaoke Hao; Xiaomeng Shi; Shuzhan Gao; Xijia Xu; Daoqiang Zhang (IEEE J. Biomed. Health Informatics, 2019)

Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease. - Xiaoke Hao; Yongjin Bao; Yingchun Guo; Ming Yu 006; Daoqiang Zhang; Shannon L. Risacher; Andrew J. Saykin; Xiaohui Yao; Li Shen 001 (Medical Image Anal., 2020)

Adaptive sparse learning using multi-template for neurodegenerative disease diagnosis. - Baiying Lei; Yujia Zhao; Zhongwei Huang; Xiaoke Hao; Feng Zhou 003; Ahmed Elazab; Jing Qin 001; Haijun Lei (Medical Image Anal., 2020)

Hierarchical Structured Sparse Learning for Schizophrenia Identification. - Mingliang Wang; Xiaoke Hao; Jiashuang Huang; Kangcheng Wang; Li Shen 001; Xijia Xu; Daoqiang Zhang; Mingxia Liu 001 (Neuroinformatics, 2020)

Identify Consistent Cross-Modality Imaging Genetic Patterns via Discriminant Sparse Canonical Correlation Analysis. - Meiling Wang 001; Wei Shao 005; Xiaoke Hao; Li Shen 001; Daoqiang Zhang (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Hypergraph Neural Network for Skeleton-Based Action Recognition. - Xiaoke Hao; Jie Li; Yingchun Guo; Tao Jiang; Ming Yu 006 (IEEE Trans. Image Process., 2021)

Identify Complex Imaging Genetic Patterns via Fusion Self-Expressive Network Analysis. - Meiling Wang 001; Wei Shao 005; Xiaoke Hao; Daoqiang Zhang (IEEE Trans. Medical Imaging, 2021)

Design and Practice of Multi-level Programming Experimental Teaching for Emerging Engineering Education. - Hua Lv; Ye Zhu; Yingchun Guo; Gang Yan 001; Yang Yu 022; Xiaoke Hao (ICCSE (3), 2022)

Identify connectome between genotypes and brain network phenotypes via deep self-reconstruction sparse canonical correlation analysis. - Meiling Wang 001; Wei Shao 005; Xiaoke Hao; Shuo Huang 001; Daoqiang Zhang (Bioinform., 2022)

JAC-Net: Joint learning with adaptive exploration and concise attention for unsupervised domain adaptive person re-identification. - Yingchun Guo; Fang Feng; Xiaoke Hao; Xi Chen 044 (Neurocomputing, 2022)

Multi-scale gradient attention guidance and adaptive style fusion for image inpainting. - Ye Zhu; Chao Wang; Shuze Geng; Yang Yu 022; Xiaoke Hao (J. Vis. Commun. Image Represent., 2022)

Machine Learning for Brain Imaging Genomics Methods: A Review. - Mei-Ling Wang 001; Wei Shao 005; Xiaoke Hao; Daoqiang Zhang (Int. J. Autom. Comput., 2023)

Multimodal Self-Paced Locality-Preserving Learning for Diagnosis of Alzheimer's Disease. - Xiaoke Hao; Ruxue Wang; Yingchun Guo; Yunjia Xiao; Ming Yu 006; Meiling Wang 001; Weibin Chen; Daoqiang Zhang (IEEE Trans. Cogn. Dev. Syst., 2023)

Identifying Modality-Consistent and Modality-Specific Features via Label-Guided Multi-Task Sparse Canonical Correlation Analysis for Neuroimaging Genetics. - Xiaoke Hao; Qihao Tan; Yingchun Guo; Yunjia Xiao; Ming Yu 006; Meiling Wang 001; Jing Qin 001; Daoqiang Zhang; Alzheimer's Disease Neuroimaging Initiative (IEEE Trans. Biomed. Eng., 2023)

A Framework on Imaging and Phenotype Information Hierarchical Graph Convolutional Networks for Identification of Autism Spectrum Disorder. - Xiaoke Hao; Mingming Ma; Yingchun Guo; Jiawang Li; Jing Qin 001; Daoqiang Zhang (ISBI, 2024)

IRNet-RS: image retargeting network via relative saliency. - Yingchun Guo; Meng Zhang; Xiaoke Hao; Gang Yan 001 (Neural Comput. Appl., 2024)

Progressive Mask Transformer With Edge Enhancement for Image Manipulation Localization. - Ye Zhu; Jian Liu; Yang Yu 022; Yingchun Guo; Xiaoke Hao (IEEE Signal Process. Lett., 2024)

Hypergraph convolutional network for longitudinal data analysis in Alzheimer's disease. - Xiaoke Hao; Jiawang Li; Mingming Ma; Jing Qin 001; Daoqiang Zhang; Feng Liu 035 (Comput. Biol. Medicine, 2024)

A review of single image super-resolution reconstruction based on deep learning. - Ming Yu 006; Jiecong Shi; Cuihong Xue; Xiaoke Hao; Gang Yan 001 (Multim. Tools Appl., 2024)

Multi-Cluster Self-Paced Diverse Learning and Feature Fusion for Autism Spectrum Disorder Identification With Resting-State fMRI. - Xiaoke Hao; Jingyi Wang; Zilong He; Yingchun Guo; Ming Yu 006; Feng Liu 035; Jing Qin 001; Daoqiang Zhang (IEEE Trans. Emerg. Top. Comput. Intell., 2024)

Efficient Deformable Convolutional Prompt for Continual Test-Time Adaptation in Medical Image Segmentation. - Shiyu Liu; Daoqiang Zhang; Xiaoke Hao (AAAI, 2025)

Reducing semantic ambiguity in domain adaptive semantic segmentation via probabilistic prototypical pixel contrast. - Xiaoke Hao; Shiyu Liu; Chuanbo Feng; Ye Zhu (Neural Networks, 2025)

Deep learning-based EEG emotion recognition: a comprehensive review. - Yuxiao Geng; Shuo Shi; Xiaoke Hao (Neural Comput. Appl., 2025)

A Hierarchical Graph Convolutional Network With Infomax-Guided Graph Embedding for Population-Based ASD Detection. - Xiaoke Hao; Mingming Ma; Jiaqing Tao; Jiahui Cao; Jing Qin 001; Feng Liu 035; Daoqiang Zhang; Dong Ming (IEEE J. Biomed. Health Informatics, 2025)