Search Results - "Variational Graph Autoencoder"

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  1. 1

    Cross-domain recommendation via knowledge distillation by Li, Xiuze, Huang, Zhenhua, Wu, Zhengyang, Wang, Changdong, Chen, Yunwen

    ISSN: 0950-7051
    Published: Elsevier B.V 28.02.2025
    Published in Knowledge-based systems (28.02.2025)
    “…Recommendation systems frequently suffer from data sparsity, resulting in less-than-ideal recommendations. A prominent solution to this problem is Cross-Domain…”
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    Journal Article
  2. 2

    Enhancing effective connection with link prediction for session-based recommendation by Wang, Hui, You, Junjie, Yi, Jianbing, Liu, Junyan, Huang, Runjie

    ISSN: 0925-2312
    Published: Elsevier B.V 07.11.2025
    Published in Neurocomputing (Amsterdam) (07.11.2025)
    “…The core objective of session-based recommendation (SBR) is to precisely capture user interest preferences from massive candidate items by modeling short-term…”
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    Journal Article
  3. 3

    Clustering Diffusion Model with Frequency-Signal Modulation for Variational Graph Autoencoders by Cheng, Junwei, Liang, Ke, Feng, Pengxing, Liu, Weixiong, Tang, Yong, He, Chaobo

    ISSN: 0162-8828, 1939-3539, 2160-9292, 1939-3539
    Published: United States IEEE 25.09.2025
    “…Variational autoencoders (VAEs) have been widely used for node clustering, with existing methods mainly focusing on enhancing the expressiveness of their…”
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  4. 4

    Variational graph autoencoder-driven balancing strategy for multimodal multi-objective optimization by Yang, Lei, Zhang, Erlei, Dang, Qianlong

    ISSN: 0020-0255
    Published: Elsevier Inc 01.09.2025
    Published in Information sciences (01.09.2025)
    “…Multimodal multi-objective optimization aims to balance the diversity and the convergence to obtain multiple complete and uniform Pareto optimal solution sets…”
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  5. 5

    Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance by Zhu, Huan, Hao, Hongxia, Yu, Liang

    ISSN: 1741-7007, 1741-7007
    Published: London BioMed Central 20.12.2023
    Published in BMC biology (20.12.2023)
    “…Background Enormous clinical and biomedical researches have demonstrated that microbes are crucial to human health. Identifying associations between microbes…”
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  6. 6

    LDA-VGHB: identifying potential lncRNA–disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine by Peng, Lihong, Huang, Liangliang, Su, Qiongli, Tian, Geng, Chen, Min, Han, Guosheng

    ISSN: 1467-5463, 1477-4054, 1477-4054
    Published: England Oxford Publishing Limited (England) 01.01.2024
    Published in Briefings in bioinformatics (01.01.2024)
    “…Long noncoding RNAs (lncRNAs) participate in various biological processes and have close linkages with diseases. In vivo and in vitro experiments have…”
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  7. 7

    Grade: Generative graph contrastive learning for multimodal recommendation by Ping, Yu-Chao, Wang, Shu-Qin, Yang, Zi-Yi, Dong, Yong-Quan, Hu, Meng-Xiang, Zhang, Pei-Lin

    ISSN: 0925-2312
    Published: Elsevier B.V 07.12.2025
    Published in Neurocomputing (Amsterdam) (07.12.2025)
    “…Multimodal recommender systems based on graph convolutional networks have made significant progress by integrating multiple modal data for item recommendation…”
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  8. 8

    Disentangled-feature and composite-prior VAE on social recommendation for new users by Li, Nuo, Guo, Bin, Liu, Yan, Yu, Zhiwen

    ISSN: 0957-4174, 1873-6793
    Published: Elsevier Ltd 01.08.2024
    Published in Expert systems with applications (01.08.2024)
    “…Social recommendation has been an effective approach to solve the new user recommendation problem based on user-item interactions and user-user social…”
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  9. 9

    Dual stream fusion link prediction for sparse graph based on variational graph autoencoder and pairwise learning by Li, Xun, Cai, Hongyun, Feng, Chuan, Zhao, Ao

    ISSN: 0306-4573
    Published: Elsevier Ltd 01.05.2025
    Published in Information processing & management (01.05.2025)
    “…Recently, link prediction methods based graph neural networks have garnered significant attention and achieved great success on large datasets. However,…”
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  10. 10

    Collaborative Decision-Reinforced Self-Supervision for Attributed Graph Clustering by Zhu, Pengfei, Li, Jialu, Wang, Yu, Xiao, Bin, Zhao, Shuai, Hu, Qinghua

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Published: United States IEEE 01.12.2023
    “…Attributed graph clustering aims to partition nodes of a graph structure into different groups. Recent works usually use variational graph autoencoder (VGAE)…”
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  11. 11

    De novo reconstruction of cell interaction landscapes from single-cell spatial transcriptome data with DeepLinc by Li, Runze, Yang, Xuerui

    ISSN: 1474-760X, 1474-7596, 1474-760X
    Published: London BioMed Central 03.06.2022
    Published in Genome Biology (03.06.2022)
    “…Based on a deep generative model of variational graph autoencoder (VGAE), we develop a new method, DeepLinc (deep learning framework for Landscapes of…”
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  12. 12

    Unveiling community structures in static networks through graph variational Bayes with evolution information by Cheng, Junwei, He, Chaobo, Han, Kunlin, Chen, Gangbin, Liang, Wanying, Tang, Yong

    ISSN: 0925-2312, 1872-8286
    Published: Elsevier B.V 01.04.2024
    Published in Neurocomputing (Amsterdam) (01.04.2024)
    “…With the rapid development of graph variational Bayes theory, some representative community detection methods have been proposed. Although these methods are…”
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  13. 13

    Predicting miRNA-Disease Associations Based On Multi-View Variational Graph Auto-Encoder With Matrix Factorization by Ding, Yulian, Lei, Xiujuan, Liao, Bo, Wu, Fang-Xiang

    ISSN: 2168-2194, 2168-2208, 2168-2208
    Published: United States IEEE 01.01.2022
    “…MicroRNAs (miRNAs) have been proved to play critical roles in diverse biological processes, including the human disease development process. Exploring the…”
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  14. 14

    Identification of microbe–disease signed associations via multi-scale variational graph autoencoder based on signed message propagation by Zhu, Huan, Hao, Hongxia, Yu, Liang

    ISSN: 1741-7007, 1741-7007
    Published: London BioMed Central 15.08.2024
    Published in BMC biology (15.08.2024)
    “…Background Plenty of clinical and biomedical research has unequivocally highlighted the tremendous significance of the human microbiome in relation to human…”
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  15. 15

    Deep graph embedding learning based on multi-variational graph autoencoders for POI recommendation by Gong, Weihua, Shen, Genhang, Zhao, Anlun, Yang, Lianghuai, Cheng, Zhen

    ISSN: 1384-5810, 1573-756X
    Published: New York Springer Nature B.V 01.07.2025
    Published in Data mining and knowledge discovery (01.07.2025)
    “…Recently, point-of-interest (POI) recommendation has become a popular research hotspot in heterogeneous location-based social network (LBSN). One major…”
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  16. 16

    Accurate identification of snoRNA targets using variational graph autoencoder to advance the redevelopment of traditional medicines by Wang, Zhina, Chen, Yangyuan, Ma, Hongming, Gao, Hong, Zhu, Yangbin, Wang, Hongwu, Zhang, Nan

    ISSN: 1663-9812, 1663-9812
    Published: Switzerland Frontiers Media S.A 06.01.2025
    Published in Frontiers in pharmacology (06.01.2025)
    “…Existing studies indicate that dysregulation or abnormal expression of small nucleolar RNA (snoRNA) is closely associated with various diseases, including lung…”
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  17. 17

    Attention-guided variational graph autoencoders reveal heterogeneity in spatial transcriptomics by Lei, Lixin, Han, Kaitai, Wang, Zijun, Shi, Chaojing, Wang, Zhenghui, Dai, Ruoyan, Zhang, Zhiwei, Wang, Mengqiu, Guo, Qianjin

    ISSN: 1467-5463, 1477-4054, 1477-4054
    Published: England Oxford Publishing Limited (England) 27.03.2024
    Published in Briefings in bioinformatics (27.03.2024)
    “…The latest breakthroughs in spatially resolved transcriptomics technology offer comprehensive opportunities to delve into gene expression patterns within the…”
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  18. 18

    Predicting Protein-Protein Interactions Using Sequence and Network Information via Variational Graph Autoencoder by Luo, Xin, Wang, Liwei, Hu, Pengwei, Hu, Lun

    ISSN: 1545-5963, 1557-9964, 1557-9964
    Published: United States IEEE 01.09.2023
    “…Protein-protein interactions (PPIs) play a critical role in the proteomics study, and a variety of computational algorithms have been developed to predict…”
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  19. 19

    GraphCVAE: Uncovering cell heterogeneity and therapeutic target discovery through residual and contrastive learning by Zhang, Zhiwei, Wang, Mengqiu, Dai, Ruoyan, Wang, Zhenghui, Lei, Lixin, Zhao, Xudong, Han, Kaitai, Shi, Chaojing, Guo, Qianjin

    ISSN: 0024-3205, 1879-0631, 1879-0631
    Published: Netherlands Elsevier Inc 15.12.2024
    Published in Life sciences (1973) (15.12.2024)
    “…Advancements in Spatial Transcriptomics (ST) technologies in recent years have transformed the analysis of tissue structure and function within spatial…”
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  20. 20

    A Variational Graph Autoencoder Aided Canonical Correlation Analysis-Based Online Abnormal Patterns Detection Method for Buildings HVAC Systems by Pan, Xiaogang, Deng, Qiao, Jiao, Yuanyuan, Chen, Zhiwen

    ISSN: 0098-3063, 1558-4127
    Published: New York IEEE 01.05.2025
    Published in IEEE transactions on consumer electronics (01.05.2025)
    “…Heating, Ventilation, and Air Conditioning (HVAC) systems have become essential components of contemporary life, extensively employed in commercial and…”
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