Distributed Branch-and-Bound Scheme for Solving the Winner Determination Problem in Combinatorial Auctions. - Satoshi Fujita; Shigeaki Tagashira; Chen Qiao; Masaya Mito (AINA, 2005)

New Critical Analysis on Global Convergence of Recurrent Neural Networks with Projection Mappings. - Chen Qiao; Zongben Xu (ISNN (3), 2007)

A critical global convergence analysis of recurrent neural networks with general projection mappings. - Chen Qiao; Zongben Xu (Neurocomputing, 2009)

On the P-critical dynamics analysis of projection recurrent neural networks. - Chen Qiao; Zongben Xu (Neurocomputing, 2010)

A comparison study on three load dispatch models in power system. - Chen Qiao; Guoli Zhang (ICMLC, 2011)

Geometric Weighting Method and Its Application on Load Dispatch in Electric Power Market. - Guoli Zhang; Chen Qiao (NL-MUA, 2011)

An augmented reality based teeth shade matching system. - Chen Qiao; Yongtian Wang; Dongdong Weng; Hongyu Qi (VRCAI, 2011)

Critical dynamics study on recurrent neural networks: Globally exponential stability. - Chen Qiao; Zongben Xu (Neurocomputing, 2012)

The UPPAM continuous-time RNN model and its critical dynamics study. - Chen Qiao; Wenfeng Jing; Zongben Xu (Neurocomputing, 2013)

The Development of an Augmented Reality Framework for Constructing Circuit Learning Aids. - Chen Qiao; Xiangdong Chen (ICHL, 2014)

Hierarchical clustering driven by cognitive features. - Chun-Zhong Li; Zongben Xu; Chen Qiao; Tao Luo 006 (Sci. China Inf. Sci., 2014)

The effective diagnosis of schizophrenia by using multi-layer RBMs deep networks. - Chen Qiao; Dongdong Lin; Shaolong Cao; Yu-Ping Wang 002 (BIBM, 2015)

Towards establishing a meaningful and practical dynamics results for the unified RNN model. - Chen Qiao; Hai-Bao Chen; Wenfeng Jing; Ke-Feng Sun (Neurocomputing, 2015)

Dynamics analysis for generic projection continuous-time RNNs with bounded matrices. - Chen Qiao; Dong Liang; Ke-Feng Sun (J. Syst. Sci. Complex., 2015)

A Study of Shelterbelt Transpiration and Cropland Evapotranspiration in an Irrigated Area in the Middle Reaches of the Heihe River in Northwestern China. - Chen Qiao; Rui Sun; Ziwei Xu; Lei Zhang; Liangyun Liu; Lvyuan Hao; Guoqing Jiang (IEEE Geosci. Remote. Sens. Lett., 2015)

Assessing the factors determining the relationship between solar-induced chlorophyll fluorescence and GPP. - Tianxiang Cui; Rui Sun 003; Chen Qiao (IGARSS, 2016)

Research on scale effect of vegetation net primary productivity. - Chen Qiao; Rui Sun 003; Tianxiang Cui (IGARSS, 2016)

The general critical analysis for continuous-time UPPAM recurrent neural networks. - Chen Qiao; Wenfeng Jing; Jian Fang 001; Yu-Ping Wang 002 (Neurocomputing, 2016)

A Novel Diagnosis Method for SZ by Deep Neural Networks. - Chen Qiao; Yan Shi; Bin Li; Tai An (DMBD, 2017)

New features in Wikiglass, a learning analytic tool for visualizing collaborative work on wikis. - Xiao Hu 001; Chengrui Yang; Chen Qiao; Xiaoyu Lu; Sam K. W. Chu (LAK, 2017)

Digitizing Dunhuang Cultural Heritage: A User Evaluation of Mogao Cave Panorama Digital Library. - Xiao Hu 001; Eric M. Y. Ho; Chen Qiao (J. Data Inf. Sci., 2017)

Critical dynamical analysis for α-UAM RNNs without diagonal nonlinear requirements. - Chen Qiao; Ke-Feng Sun; Wenfeng Jing; Yan Shi (J. Intell. Fuzzy Syst., 2017)

Estimating Diurnal Courses of Gross Primary Production for Maize: A Comparison of Sun-Induced Chlorophyll Fluorescence, Light-Use Efficiency and Process-Based Models. - Tianxiang Cui; Rui Sun 003; Chen Qiao; Qiang Zhang; Tao Yu; Gang Liu; Zhigang Liu 012 (Remote. Sens., 2017)

Discovering Student Behavior Patterns from Event Logs: Preliminary Results on a Novel Probabilistic Latent Variable Model. - Chen Qiao; Xiao Hu 001 (ICALT, 2018)

A Deep-Layer Feature Selection Method Based on Deep Neural Networks. - Chen Qiao; Ke-Feng Sun; Bin Li (ICSI (2), 2018)

Fine-Grained Resource Management for Edge Computing Satellite Networks. - Feng Wang 049; Dingde Jiang; Sheng Qi; Chen Qiao; Houbing Song (GLOBECOM, 2019)

Measuring Knowledge Gaps in Student Responses by Mining Networked Representations of Texts. - Chen Qiao; Xiao Hu 001 (LAK, 2019)

Dynamic Computing Resource Adjustment in Edge Computing Satellite Networks. - Feng Wang 049; Dingde Jiang; Sheng Qi; Chen Qiao; Jiping Xiong (SimuTools, 2019)

Text classification for cognitive domains: A case using lexical, syntactic and semantic features. - Chen Qiao; Xiao Hu 001 (J. Inf. Sci., 2019)

On the Flexible Dynamics Analysis for the Unified Discrete-Time RNNs. - Chen Qiao; Bao Guo (Neural Process. Lett., 2019)

Biomarkers Selection of Abnormal Functional Connections in Schizophrenia with $ { mathbf{ ell }}_{{{ mathbf{2, 1 - 2}}}} $-Norm Based Sparse Regularization Feature Selection Method. - Na Gao; Chen Qiao; Shun Qi; Kai Ren; Jian Chen; Hanfeng Fang (ICIC (2), 2020)

Flexible Resources Planning for Bulk Energy System With High Penetration of Renewable Energy Based on Bash Game. - Pan Hu; Cao Zixun; Hongkun Chen; Wang Yi 007; Chang Ye; Chen Qiao; Yimin Qian (IEEE Access, 2020)

What predicts student satisfaction with MOOCs: A gradient boosting trees supervised machine learning and sentiment analysis approach. - Khe Foon Hew; Xiang Hu; Chen Qiao; Ying Tang 005 (Comput. Educ., 2020)

Log-sum enhanced sparse deep neural network. - Chen Qiao; Yan Shi; Yu-Xian Diao; Vince D. Calhoun; Yu-Ping Wang 002 (Neurocomputing, 2020)

A neural knowledge graph evaluator: Combining structural and semantic evidence of knowledge graphs for predicting supportive knowledge in scientific QA. - Chen Qiao; Xiao Hu 001 (Inf. Process. Manag., 2020)

A joint neural network model for combining heterogeneous user data sources: An example of at-risk student prediction. - Chen Qiao; Xiao Hu 001 (J. Assoc. Inf. Sci. Technol., 2020)

SRS-DNN: a deep neural network with strengthening response sparsity. - Chen Qiao; Bin Gao; Yan Shi (Neural Comput. Appl., 2020)

Feature Back-Tracking with Sparse Deep Belief Networks. - Chen Qiao; Jiajia Li; Xuewu Zhang 004; Cheng Zhang; Wenfeng Jing; Danglin Yang (FSDM, 2021)

Biomarkers Selection based on FS-TNNR in Schizophrenia. - Jiajia Li; Chen Qiao; Kai Ren; Jian Chen; Hanfeng Fang (ICBBT, 2021)

How social instant messaging questions affect replies: a randomised controlled experiment. - Ying Tang 005; Khe Foon Hew; Xinyue Yuan; Chen Qiao (Behav. Inf. Technol., 2021)

A deep autoencoder with sparse and graph Laplacian regularization for characterizing dynamic functional connectivity during brain development. - Chen Qiao; Xin-Yu Hu; Li Xiao 002; Vince D. Calhoun; Yu-Ping Wang 002 (Neurocomputing, 2021)

An Adaboost Based Link Planning Scheme in Space-Air-Ground Integrated Networks. - Feng Wang 049; Dingde Jiang; Sheng Qi; Chen Qiao (Mob. Networks Appl., 2021)

A Dynamic Resource Scheduling Scheme in Edge Computing Satellite Networks. - Feng Wang 049; Dingde Jiang; Sheng Qi; Chen Qiao; Lei Shi 008 (Mob. Networks Appl., 2021)

Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental study. - Chen Qiao; Lan Yang 010; Vince D. Calhoun; Zong-Ben Xu; Yu-Ping Wang 002 (Neural Networks, 2021)

Representation learning of RNA velocity reveals robust cell transitions. - Chen Qiao; Yuanhua Huang (Proc. Natl. Acad. Sci. USA, 2021)

Graph Convolutional Network with Attention Mechanism for Discovering the Brain's Abnormal Activity of Attention Deficit Hyperactivity Disorder. - Aiju Yu; Longyun Chen; Chen Qiao (CISP-BMEI, 2022)

Deep belief networks with self-adaptive sparsity. - Chen Qiao; Lan Yang 010; Yan Shi; Hanfeng Fang; Yanmei Kang (Appl. Intell., 2022)

Biomarkers identification for Schizophrenia via VAE and GSDAE-based data augmentation. - Qi Huang; Chen Qiao; Kaili Jing; Xu Zhu; Kai Ren (Comput. Biol. Medicine, 2022)

Deep Learning in Neuroimaging: Promises and challenges. - Weizheng Yan; Gang Qu 002; Wenxing Hu; Anees Abrol; Biao Cai; Chen Qiao; Sergey M. Plis; Yu-Ping Wang 002; Jing Sui; Vince D. Calhoun (IEEE Signal Process. Mag., 2022)

Multiview deep learning based on tensor decomposition and its application in fault detection of overhead contact systems. - Xuewu Zhang 004; Yansheng Gong; Chen Qiao; Wenfeng Jing (Vis. Comput., 2022)

A Machine Learning Approach for Understanding the Educational Foci and Technical Solutions of AIED. - Hahohua Liu; Shihui Feng; Chen Qiao (L@S, 2023)

An explainable autoencoder with multi-paradigm fMRI fusion for identifying differences in dynamic functional connectivity during brain development. - Faming Xu; Chen Qiao; Huiyu Zhou 001; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (Neural Networks, 2023)

Leveraging Semantic Facets for Automatic Assessment of Short Free Text Answers. - Chen Qiao; Xiao Hu 001 (IEEE Trans. Learn. Technol., 2023)

Sparse non-convex regularization based explainable DBN in the analysis of brain abnormalities in schizophrenia. - Jiajia Li; Faming Xu; Na Gao; Yuanqiang Zhu; Yuewen Hao; Chen Qiao (Comput. Biol. Medicine, 2023)

FRCNN-AA-CIF: An automatic detection model of colon polyps based on attention awareness and context information fusion. - Ruolin Gong; SiJie He; Tiantian Tian; Jian Chen; Yuewen Hao; Chen Qiao (Comput. Biol. Medicine, 2023)

Explainable Multimodal Deep Dictionary Learning to Capture Developmental Differences From Three fMRI Paradigms. - Lan Yang 010; Chen Qiao; Huiyu Zhou 001; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2023)

Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity. - Chen Qiao; Bin Gao; Yuechen Liu; Xin-Yu Hu; Wenxing Hu; Vince D. Calhoun; Yu-Ping Wang 002 (Medical Image Anal., 2023)

Explainable spatio-temporal graph evolution learning with applications to dynamic brain network analysis during development. - Longyun Chen; Chen Qiao; Kai Ren; Gang Qu 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (NeuroImage, 2024)

Reliable imputation of spatial transcriptomes with uncertainty estimation and spatial regularization. - Chen Qiao; Yuanhua Huang (Patterns, 2024)

Lightweight fungal spore detection based on improved YOLOv5 in natural scenes. - Kaiyu Li; Chen Qiao; Xinyi Zhu; Yuzhaobi Song; Lingxian Zhang; Wei Gao; Yong Wang (Int. J. Mach. Learn. Cybern., 2024)

A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development. - Yingying Wang; Chen Qiao; Gang Qu 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2024)

An explainable spatio-temporal graph convolutional network for the biomarkers identification of ADHD. - Longyun Chen; Yuhui Yang; Aiju Yu; Shuo Guo; Kai Ren; Qinfang Liu; Chen Qiao (Biomed. Signal Process. Control., 2025)

T-CADiff: Conditional guidance based diffusion model for medical image segmentation. - Han Yang; Jiao Zhang; Lijiang Shao; Chao Jin; Jian Yang; Chen Qiao (Biomed. Signal Process. Control., 2025)

Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain. - Lan Yang 010; Chen Qiao; Takafumi Kanamori; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (Neural Networks, 2025)

GATE: Adaptive Learning with Working Memory by Information Gating in Multi-lamellar Hippocampal Formation. - Yuechen Liu; Zishun Wang; Chen Qiao; Zongben Xu (CoRR, 2025)

A Deep Spatio-Temporal Architecture for Dynamic Effective Connectivity Network Analysis Based on Dynamic Causal Discovery. - Faming Xu; Yiding Wang; Chen Qiao; Gang Qu 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (CoRR, 2025)

An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis. - Bin Gao; Aiju Yu; Chen Qiao; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2025)