Search Results - "Variational graph autoencoder"

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  1. 1

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

    ISSN: 0020-0255, 1872-6291
    Published: Elsevier Inc 01.09.2023
    Published in Information sciences (01.09.2023)
    “…Learning representations of both user interests and item characteristics is essentially important for recommendation tasks. Although graph neural network-based…”
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    Journal Article
  2. 2

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

    ISSN: 2154-512X
    Published: 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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    Conference Proceeding
  3. 3

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

    Published: IEEE 06.12.2021
    “…Despite decades of research, understanding human manipulation activities is, and has always been, one of the most attractive and challenging research topics in…”
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    Conference Proceeding
  4. 4

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

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 25.10.2021
    Published in arXiv.org (25.10.2021)
    “…Despite decades of research, understanding human manipulation activities is, and has always been, one of the most attractive and challenging research topics in…”
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    Paper
  5. 5

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

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 29.10.2021
    Published in 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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    Paper
  6. 6

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

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 05.07.2020
    Published in 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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    Paper