Výsledky vyhledávání - "graph autoencoder"

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  1. 1

    VIGA: A variational graph autoencoder model to infer user interest representations for recommendation Autor Gan, Mingxin, Zhang, Hang

    ISSN: 0020-0255, 1872-6291
    Vydáno: Elsevier Inc 01.09.2023
    Vydáno v Information sciences (01.09.2023)
    “… To overcome these limitations, we propose a variational inference-based graph autoencoder (VIGA) model to explore a multivariate distribution over latent representations for recommendation…”
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    Journal Article
  2. 2

    Spatiotemporal Graph Autoencoder Network for Skeleton-Based Human Action Recognition Autor Abduljalil, Hosam, Elhayek, Ahmed, Marish Ali, Abdullah, Alsolami, Fawaz

    ISSN: 2673-2688, 2673-2688
    Vydáno: Basel MDPI AG 01.09.2024
    Vydáno v AI (Basel) (01.09.2024)
    “… In this study, we propose a novel, highly accurate spatiotemporal graph autoencoder network for HAR, designated as GA-GCN…”
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    Journal Article
  3. 3

    Graph-based learning for sleep microarchitecture: a hybrid graph autoencoder and graph attention network approach Autor Kurisinkal Augustine, Amala Ann, Vaidhehi

    ISSN: 2320-6071, 2320-6012
    Vydáno: 30.10.2025
    “…: We developed a graph autoencoder (GAE) combined with a Graph attention network (GAT) to analyze polysomnography (PSG…”
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    Journal Article
  4. 4

    Robust Graph Autoencoder-Based Detection of False Data Injection Attacks Against Data Poisoning in Smart Grids Autor Takiddin, Abdulrahman, Ismail, Muhammad, Atat, Rachad, Davis, Katherine R., Serpedin, Erchin

    ISSN: 2691-4581, 2691-4581
    Vydáno: IEEE 01.03.2024
    “…) of existing detectors significantly deteriorate by up to <inline-formula><tex-math notation="LaTeX">\text{9}\text{--}\text{29}{\%}</tex-math></inline-formula> when subject to data poisoning…”
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  5. 5

    An Edge Feature Inclusive Variational Graph Autoencoder for Pet-Driven Alzheimer's Diagnosis Autor Gurbuz, Saruhan Mete, Adel, Mouloud

    ISSN: 2154-512X
    Vydáno: IEEE 13.10.2025
    “… We propose GINEVGAE(Modified Graph Isomorphism Network with Variational Graph Autoencoder, a novel variational graph autoencoder that leverages GINEConv…”
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    Konferenční příspěvek
  6. 6

    MSLTE: multiple self-supervised learning tasks for enhancing EEG emotion recognition Autor Li, Guangqiang, Chen, Ning, Niu, Yixiang, Xu, Zhangyong, Dong, Yuxuan, Jin, Jing, Zhu, Hongqin

    ISSN: 1741-2552, 1741-2552
    Vydáno: England 01.04.2024
    Vydáno v Journal of neural engineering (01.04.2024)
    “… learning-based feature reconstruction tasks combining masked graph autoencoders (GAE) are constructed…”
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  7. 7

    A Variational Graph Autoencoder for Manipulation Action Recognition and Prediction Autor Akyol, Gamze, Sariel, Sanem, Aksoy, Eren Erdal

    Vydáno: IEEE 06.12.2021
    “… Different from the related works, we here introduce a deep graph autoencoder to jointly learn recognition and prediction…”
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  8. 8

    A Variational Graph Autoencoder for Manipulation Action Recognition and Prediction Autor Akyol, Gamze, Sariel, Sanem, Eren Erdal Aksoy

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 25.10.2021
    Vydáno v arXiv.org (25.10.2021)
    “… Different from the related works, we here introduce a deep graph autoencoder to jointly learn recognition and prediction…”
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  9. 9

    Cross-Group Brain Network Topology Propagation Model with Graph Attention Mechanism Autor Yu, Jing, Li, Shengrong, Ma, Kai, Wan, Peng, Sun, Liang, Zhu, Qi

    Vydáno: IEEE 10.11.2023
    “… Firstly, we extract the functional brain network topology of healthy subjects and patients and adaptively evaluate the centrality distribution of brain regions by the PageRank algorithm…”
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  10. 10

    CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics Autor Bafna, Mihir, Li, Hechen, Zhang, Xiuwei

    ISSN: 1367-4803, 1367-4811, 1367-4811
    Vydáno: England Oxford University Press 30.06.2023
    Vydáno v Bioinformatics (Oxford, England) (30.06.2023)
    “… However, in reality, the two processes do not exist in isolation and are subject to spatial constraints…”
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  11. 11

    A Graph-Based Generative Adversarial Network Model for Inferring Task-State from Resting-State Functional Connectivity Networks Autor Jin, Tao, Guan, Hongzheng, Xiao, Li, Qu, Gang, Wang, Yu-Ping

    ISSN: 2379-190X
    Vydáno: IEEE 06.04.2025
    “… In this paper, we propose a Multiple Graph Autoencoder based Generative Adversarial Network (MGAE-GAN) model to enable the inference of ts-FCNs from rs-FCNs…”
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  12. 12

    Probing the Substructure of Jets With Machine Learning Autor Athanasakos, Dimitrios

    ISBN: 9798297994232
    Vydáno: ProQuest Dissertations & Theses 01.01.2025
    “… We introduce Jet Flow Networks (JFNs), a novel deep learning framework that uses reclustered subjects as input…”
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    Dissertation
  13. 13

    Graph Based Business Process Anomaly Detection with Edge Feature Reconstruction and Advanced Linear Networks Autor Ayaz, Teoman Berkay, Cevik, Rabia, Ozcan, Alper, Akbulut, Akhan

    ISSN: 2996-4393
    Vydáno: IEEE 23.05.2025
    “…Business Process Management (BPM) as an inter-disciplinary field between Managerial Sciences and Computer Science is a subject ever-increasing in importance…”
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  14. 14

    On the Power of Edge Independent Graph Models Autor Chanpuriya, Sudhanshu, Musco, Cameron, Sotiropoulos, Konstantinos, Tsourakakis, Charalampos E

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 29.10.2021
    Vydáno v arXiv.org (29.10.2021)
    “… Such models include both the classic Erd\"{o}s-R\'{e}nyi and stochastic block models, as well as modern generative models such as NetGAN, variational graph autoencoders, and CELL…”
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  15. 15

    Predicting potential drug targets and repurposable drugs for COVID-19 via a deep generative model for graphs Autor Ray, Sumanta, Lall, Snehalika, Mukhopadhyay, Anirban, Bandyopadhyay, Sanghamitra, Schönhuth, Alexander

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 05.07.2020
    Vydáno v arXiv.org (05.07.2020)
    “…Coronavirus Disease 2019 (COVID-19) has been creating a worldwide pandemic situation. Repurposing drugs, already shown to be free of harmful side effects, for…”
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