Search Results - Variation Graph Autoencoder (VGAE)

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  1. 1

    Optimization of Graph Convolutional Networks with Variational Graph Autoencoder Architecture for 3D Face Reconstruction Task by Batarfi, Mahfoudh M., Mareboyana, Manohar

    ISSN: 2768-0754
    Published: IEEE 08.05.2024
    “… To surmount these obstacles, the study embarks on the optimization of a Variational Graph Autoencoder (VGAE…”
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    Conference Proceeding
  2. 2

    CVAM: CNA Profile Inference of the Spatial Transcriptome Based on the VGAE and HMM by Ma, Jian, Guo, Jingjing, Fan, Zhiwei, Zhao, Weiling, Zhou, Xiaobo

    ISSN: 2218-273X, 2218-273X
    Published: Switzerland MDPI AG 28.04.2023
    Published in Biomolecules (Basel, Switzerland) (28.04.2023)
    “… With the development of spatial transcriptome technologies, it is urgent to develop new tools to identify genomic variation from the spatial transcriptome…”
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    Journal Article
  3. 3

    Self-Supervised Variational Graph Autoencoder for System-Level Anomaly Detection by Zhang, Le, Cheng, Wei, Xing, Ji, Chen, Xuefeng, Nie, Zelin, Zhang, Shuo, Hong, Junying, Xu, Zhao

    ISSN: 0018-9456, 1557-9662
    Published: New York IEEE 2023
    “… However, most industrial scenarios are without graphs. Hence, a self-supervised variational graph autoencoders (SS-VGAE) method is proposed…”
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    Journal Article
  4. 4

    Enhancing the Performance of VGAE Architectures for Reconstruction High-Quality 3D Faces by Batarfi, Mahfoudh M

    ISBN: 9798382319131
    Published: ProQuest Dissertations & Theses 01.01.2024
    “…This research investigates methods to enhance the performance of Variational Graph Autoencoder (VGAE…”
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    Dissertation
  5. 5

    DCMF-PPI: a protein-protein interaction predictor based on dynamic condition and multi-feature fusion by Chen, Siqi, Zheng, Anhong, Yu, Weichi, Zhan, Chao

    ISSN: 1471-2105, 1471-2105
    Published: London BioMed Central 15.10.2025
    Published in BMC bioinformatics (15.10.2025)
    “… Nevertheless, these approaches frequently overlook the dynamic nature of protein and PPI structures during cellular processes, including conformational alterations and variations in binding…”
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    Journal Article
  6. 6

    Hierarchical Graph Neural Network Based on Semi-Implicit Variational Inference by Su, Hai-Long, Li, Zhi-Peng, Zhu, Xiao-Bo, Yang, Li-Na, Gribova, Valeriya, Filaretov, Vladimir Fedorovich, Cohn, Anthony G., Huang, De-Shuang

    ISSN: 2379-8920, 2379-8939
    Published: Piscataway IEEE 01.06.2023
    “… Recently, variational graph autoencoder (VGAE) has been proposed to solve this problem. However, the distributional assumptions in the variational family restrict the variational inference (VI…”
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    Journal Article