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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]:1 TC[Scopus]:3 | Submit date：2023/12/13
Deep Generative Models  Imputation  Missing Data  Missing Not At Random  Variational Autoencoder  
Generative AI for brain image computing and brain network computing: a review Review article
2023
Authors:  Gong,Changwei;  Jing,Changhong;  Chen,Xuhang;  Pun,Chi Man;  Huang,Guoli; et al.
Favorite | TC[WOS]:31 TC[Scopus]:42 | Submit date：2023/08/03
Brain Imaging  Brain Network  Diffusion Model  Generative Adversarial Network  Generative Models  Variational Autoencoder  
Field-aware Variational Autoencoders for Billion-scale User Representation Learning Conference paper
Ge Fan, Chaoyun Zhang, Junyang Chen, Baopu Li, Zenglin Xu, Yingjie Li, Luyu Peng, Zhiguo Gong. Field-aware Variational Autoencoders for Billion-scale User Representation Learning[C], 2022, 3413-3425.
Authors:  Ge Fan;  Chaoyun Zhang;  Junyang Chen;  Baopu Li;  Zenglin Xu; et al.
Favorite | TC[WOS]:4 TC[Scopus]:6 | Submit date：2022/08/29
Lookalike Systems  Recommender Systems  User Representation Learning  Variational Autoencoder  
A deep generative approach for crash frequency model with heterogeneous imbalanced data Journal article
Ding, Hongliang, Lu, Yuhuan, Sze, N. N., Chen, Tiantian, Guo, Yanyong, Lin, Qinghai. A deep generative approach for crash frequency model with heterogeneous imbalanced data[J]. Analytic Methods in Accident Research, 2022, 34, 100212.
Authors:  Ding, Hongliang;  Lu, Yuhuan;  Sze, N. N.;  Chen, Tiantian;  Guo, Yanyong; et al.
Favorite | TC[WOS]:36 TC[Scopus]:38  IF:12.5/12.3 | Submit date：2022/05/13
Augmented Variational Autoencoder  Crash Frequency Model  Imbalanced Crash Data  Machine Learning