Suchergebnisse - graph convolutional autoencoder (GCAE)

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  1. 1

    Graph convolutional autoencoder model for the shape coding and cognition of buildings in maps von Yan, Xiongfeng, Ai, Tinghua, Yang, Min, Tong, Xiaohua

    ISSN: 1365-8816, 1362-3087, 1365-8824
    Veröffentlicht: Abingdon Taylor & Francis 04.03.2021
    “… A graph convolutional autoencoder (GCAE) model comprising graph convolution and autoencoder architecture is proposed to analyze …”
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    Journal Article
  2. 2

    GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder von Li, Lei, Wang, Yu-Tian, Ji, Cun-Mei, Zheng, Chun-Hou, Ni, Jian-Cheng, Su, Yan-Sen

    ISSN: 1553-7358, 1553-734X, 1553-7358
    Veröffentlicht: United States Public Library of Science 10.12.2021
    Veröffentlicht in PLoS computational biology (10.12.2021)
    “… , diagnosis and treatment of extraordinary diseases. In this study, we presented a novel model named Graph Convolutional Autoencoder for miRNA-Disease Association Prediction (GCAEMDA …”
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    Journal Article
  3. 3

    Seismic damage identification by graph convolutional autoencoder using adjacency matrix based on structural modes von Kim, Minkyu, Song, Junho

    ISSN: 0098-8847, 1096-9845
    Veröffentlicht: Bognor Regis Wiley Subscription Services, Inc 01.02.2024
    Veröffentlicht in Earthquake engineering & structural dynamics (01.02.2024)
    “… ‐time damage identification by a graph convolutional autoencoder (GCAE) based on seismic responses of the structural system …”
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    Journal Article
  4. 4

    Semi-supervised overlapping community detection in attributed graph with graph convolutional autoencoder von He, Chaobo, Zheng, Yulong, Cheng, Junwei, Tang, Yong, Chen, Guohua, Liu, Hai

    ISSN: 0020-0255, 1872-6291
    Veröffentlicht: Elsevier Inc 01.08.2022
    Veröffentlicht in Information sciences (01.08.2022)
    “… •An end-to-end method SSGCAE for overlapping community detection is proposed.•SSGCAE is based on graph convolutional autoencoder driven by community detection …”
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    Journal Article
  5. 5

    Unsupervised Multimodal Change Detection Based on Structural Relationship Graph Representation Learning von Chen, Hongruixuan, Yokoya, Naoto, Wu, Chen, Du, Bo

    ISSN: 0196-2892, 1558-0644
    Veröffentlicht: New York IEEE 01.01.2022
    Veröffentlicht in IEEE transactions on geoscience and remote sensing (01.01.2022)
    “… Then, a structural relationship graph convolutional autoencoder (SR-GCAE) is proposed to learn robust and representative features from graphs …”
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    Journal Article
  6. 6

    Blockchain-based decentralized smart healthcare using improved wild horse optimizer with Graph Convolutional Autoencoder in IoT environment von Escorcia-Gutierrez, José, Torres-Torres, Melitsa, Soto-Diaz, Roosvel, Soto, Carlos

    ISSN: 2666-3074, 2666-3074
    Veröffentlicht: Elsevier B.V 01.12.2026
    “… The Internet of Things (IoT) continues to expand by incorporating physical devices, software, computing systems, and hardware that facilitate communication and …”
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    Journal Article
  7. 7

    Human-related anomalous event detection via spatial-temporal graph convolutional autoencoder with embedded long short-term memory network von Li, Nanjun, Chang, Faliang, Liu, Chunsheng

    ISSN: 0925-2312, 1872-8286
    Veröffentlicht: Elsevier B.V 14.06.2022
    Veröffentlicht in Neurocomputing (Amsterdam) (14.06.2022)
    “… Our network is established on a Spatial-temporal Graph Convolutional …”
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    Journal Article
  8. 8

    Self-supervised community detection in multiplex networks with graph convolutional autoencoder von Liu, Xingyu, Cheng, Junwei, Cheng, Hao, He, Chaobo, Chen, Qimai, Guan, Quanlong

    ISSN: 2768-1904
    Veröffentlicht: IEEE 24.05.2023
    “… However, existing methods that combine graph embedding and downstream tasks still face two challenges …”
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  9. 9

    Unsupervised Multimodal Change Detection Based on Structural Relationship Graph Representation Learning von Chen, Hongruixuan, Yokoya, Naoto, Wu, Chen, Du, Bo

    ISSN: 2331-8422
    Veröffentlicht: Ithaca Cornell University Library, arXiv.org 03.10.2022
    Veröffentlicht in arXiv.org (03.10.2022)
    “… Then, a structural relationship graph convolutional autoencoder (SR-GCAE) is proposed to learn robust and representative features from graphs …”
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    Paper
  10. 10

    멀티모달 오토인코더 앙상블 기반의 URL 문자열 및 HTML 그래프를 활용한 피싱 웹페이지 탐지 von 윤준호, 최석훈, 김혜정, 부석준

    ISSN: 2383-630X, 2383-6296
    Veröffentlicht: 한국정보과학회 01.06.2025
    Veröffentlicht in Chŏngbo Kwahakhoe nonmunji (01.06.2025)
    “… To address this, we propose a multimodal ensemble-based phishing detection method that leverages both URL strings and HTML graph data …”
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    Journal Article
  11. 11

    Graph Anomaly Detection With Disentangled Prototypical Autoencoder for Phishing Scam Detection in Cryptocurrency Transactions von Kang, Junha, Buu, Seok-Jun

    ISSN: 2169-3536, 2169-3536
    Veröffentlicht: Piscataway IEEE 2024
    Veröffentlicht in IEEE access (2024)
    “… In this paper, we present Disentangled Prototypical Graph Convolutional Autoencoder, which is optimized for detecting anomalies in cryptocurrency transactions …”
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    Journal Article
  12. 12

    Enhancing Anomaly Detection in Attributed Networks Using Proximity Preservation and Advanced Embedding Techniques von Khan, Wasim, Ishrat, Mohammad, Nadeem Ahmed, Mohammad, Abidin, Shafiqul, Husain, Mohammad, Izhar, Mohd, Zamani, Abu Taha, Rashid Hussain, Mohammad, Ali, Arshad

    ISSN: 2169-3536, 2169-3536
    Veröffentlicht: IEEE 2025
    Veröffentlicht in IEEE access (2025)
    “… To address this, we propose a novel approach that combines a Graph Convolution Auto encoder (GCAE …”
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    Journal Article