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Generative broad Bayesian (GBB) imputer for missing data imputation with uncertainty quantification Journal article
Kuok, Sin Chi, Yuen, Ka Veng, Dodwell, Tim, Girolami, Mark. Generative broad Bayesian (GBB) imputer for missing data imputation with uncertainty quantification[J]. Knowledge-Based Systems, 2024, 301, 112272.
Authors:  Kuok, Sin Chi;  Yuen, Ka Veng;  Dodwell, Tim;  Girolami, Mark
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:7.2/7.4 | Submit date：2024/08/05
Bayesian Inference  Broad Bayesian Learning  Imputation  Missing Data  Uncertainty Quantification  
manymome: An R package for computing the indirect efects, conditional efects, and conditional indirect efects, standardized or unstandardized, and their bootstrap confdence intervals, in many (though not all) models Journal article
Cheung, Shu Fai, Cheung, Sing Hang. manymome: An R package for computing the indirect efects, conditional efects, and conditional indirect efects, standardized or unstandardized, and their bootstrap confdence intervals, in many (though not all) models[J]. Behavior Research Methods, 2024, 56, 4862-4882.
Authors:  Cheung, Shu Fai;  Cheung, Sing Hang
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:4.6/7.2 | Submit date：2024/01/03
Bootstrapping  Conditional Indirect Effect  Mediation  Missing Data  Moderation  Regression  Structural Equation Modeling  
A novel and efficient method for real-time simulating spatial and temporal evolution of coastal urban pluvial flood without drainage network Journal article
Qin, Jintao, Gao, Liang, Lin, Kairong, Shen, Ping. A novel and efficient method for real-time simulating spatial and temporal evolution of coastal urban pluvial flood without drainage network[J]. Environmental Modelling and Software, 2024, 172, 105888.
Authors:  Qin, Jintao;  Gao, Liang;  Lin, Kairong;  Shen, Ping
Favorite | TC[WOS]:3 TC[Scopus]:3  IF:4.8/5.2 | Submit date：2024/02/22
Drainage Data Missing  Equivalent Drainage Hydrodynamic Model  Flood Real-time Simulation  Hybrid Method  Immediate Calibration  Machine Learning  
Deep Generative Imputation Model for Missing Not At Random Data Conference paper
Jialei Chen, Yuanbo Xu, Pengyang Wang, Yongjian Yang. Deep Generative Imputation Model for Missing Not At Random Data[C]:ASSOC COMPUTING MACHINERY1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES, 2023, 316 - 325.
Authors:  Jialei Chen;  Yuanbo Xu;  Pengyang Wang;  Yongjian Yang
Favorite | TC[WOS]:2 TC[Scopus]:3 | Submit date：2023/12/13
Deep Generative Models  Imputation  Missing Data  Missing Not At Random  Variational Autoencoder  
A Survey on Incomplete Multiview Clustering Journal article
Jie Wen, Zheng Zhang, Lunke Fei, Bob Zhang, Yong Xu, Zhao Zhang, Jinxing Li. A Survey on Incomplete Multiview Clustering[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 53(2), 1136-1149.
Authors:  Jie Wen;  Zheng Zhang;  Lunke Fei;  Bob Zhang;  Yong Xu; et al.
Favorite | TC[WOS]:112 TC[Scopus]:115  IF:8.6/8.7 | Submit date：2023/01/30
Data Mining  Missing Views  Incomplete Multiview Clustering (Imc)  Multiview Learning  
An improved method of handling missing values in the analysis of sample entropy for continuous monitoring of physiological signals Journal article
Dong X., Chen C., Geng Q., Cao Z., Chen X., Lin J., Jin Y., Zhang Z., Shi Y., Zhang X.D.. An improved method of handling missing values in the analysis of sample entropy for continuous monitoring of physiological signals[J]. Entropy, 2019, 21(3).
Authors:  Dong X.;  Chen C.;  Geng Q.;  Cao Z.;  Chen X.; et al.
Adobe PDF | Favorite | TC[WOS]:20 TC[Scopus]:20  IF:2.1/2.2 | Submit date：2021/03/03
Complexity  Medical Information  Missing Values  Physiological Data  Sample Entropy  
An Improved Method for Using Sample Entropy to Reveal Medical Information in Data from Continuously Monitored Physiological Signals Conference paper
Dong, Xinzheng, Chen, Chang, Geng, Qingshan, Cao, Zhixin, Jin, Yu, Shi, Yan, Zhang, Xiaohua Douglas. An Improved Method for Using Sample Entropy to Reveal Medical Information in Data from Continuously Monitored Physiological Signals[C], 2019, 2502-2506.
Authors:  Dong, Xinzheng;  Chen, Chang;  Geng, Qingshan;  Cao, Zhixin;  Jin, Yu; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2022/04/15
Complexity  Entropy  Missing Values  Physiological Data  Time Series  
Ensemble correlation-based low-rank matrix completion with applications to traffic data imputation Journal article
Chen, Xiaobo, Wei, Zhongjie, Li, Zuoyong, Liang, Jun, Cai, Yingfeng, Zhang, Bob. Ensemble correlation-based low-rank matrix completion with applications to traffic data imputation[J]. KNOWLEDGE-BASED SYSTEMS, 2017, 132, 249-262.
Authors:  Chen, Xiaobo;  Wei, Zhongjie;  Li, Zuoyong;  Liang, Jun;  Cai, Yingfeng; et al.
Favorite | TC[WOS]:51 TC[Scopus]:61  IF:7.2/7.4 | Submit date：2018/10/30
Missing Data  Low-rank Matrix Completion  Nearest Neighbor  Pearson's Correlation  Ensemble Learning  
Model free feature screening for ultrahigh dimensional models with responses missing at random Journal article
Lai, P., Liu, Y., Liu, Z., Wan, Y.. Model free feature screening for ultrahigh dimensional models with responses missing at random[J]. Computational Statistics and Data Analysis, 2017, 201-216.
Authors:  Lai, P.;  Liu, Y.;  Liu, Z.;  Wan, Y.
Favorite | TC[WOS]:29 TC[Scopus]:33  IF:1.5/1.7 | Submit date：2022/07/27
Ultrahigh Dimensional Data  Missing At Random  Feature Screening  Sure Screening Property  
Model free feature screening for ultrahigh dimensional data with responses missing at random Journal article
Lai, Peng, Liu, Yiming, Liu, Zhi, Wan, Yi. Model free feature screening for ultrahigh dimensional data with responses missing at random[J]. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2017, 105, 201-216.
Authors:  Lai, Peng;  Liu, Yiming;  Liu, Zhi;  Wan, Yi
Favorite | TC[WOS]:29 TC[Scopus]:33  IF:1.5/1.7 | Submit date：2018/10/30
Ultrahigh Dimensional Data  Missing At Random  Feature Screening  Sure Screening Property