Anomaly Detection on Static and Dynamic Graphs Using Graph Convolutional Neural Networks-Reference-Cited by-同舟云学术

Anomaly Detection on Static and Dynamic Graphs Using Graph Convolutional Neural Networks

Published:2022 Issue: Volume: Page:227-248
ISSN:1860-949X
Container-title:Robotics and AI for Cybersecurity and Critical Infrastructure in Smart Cities
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Author:

Rida Amani Abou,Amhaz Rabih,Parrend Pierre

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-96737-6_12

Reference56 articles.

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2. Shen Wang, P.S.Y.: Chapter 26 Graph neural networks in anomaly detection, pp. 558–578. https://graph-neural-networks.github.io/static/file/chapter26.pdf

3. Xu, M.: Understanding graph embedding methods and their applications. arXiv:2012.08019 (2020)

4. Wu, Z., Pan, S., Chen, F., Long, G., Zhang, C., Philip, S.Y.: A comprehensive survey on graph neural networks. IEEE Trans. Neural Netw. Learn. Syst. 32(1), 4–24 (2020)

5. Zhou, R., Zhang, Q., Zhang, P., Niu, L., Lin, X.: Anomaly detection in dynamic attributed networks. Neural Comput. Appl. 33(6), 2125–2136 (2021)

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