Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning-Reference-Cited by-同舟云学术

Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
language:
Short-container-title:

Author:

Duan Jingcan¹^ORCID,Zhang Pei¹^ORCID,Wang Siwei²^ORCID,Hu Jingtao¹^ORCID,Jin Hu¹^ORCID,Zhang Jiaxin¹^ORCID,Zhou Haifang¹^ORCID,Liu Xinwang¹^ORCID

Affiliation:

1. National University of Defense Technology, Changsha, China

2. Intelligent Game and Decision Lab, Beijing, China

Funder

the National Key R&D Program of China

the National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3612064

Reference44 articles.

1. Beyond Low-frequency Information in Graph Convolutional Networks

2. LOF

3. Ziwei Chai Siqi You Yang Yang Shiliang Pu Jiarong Xu Haoyang Cai and Weihao Jiang. [n. d.]. Can Abnormality be Detected by Graph Neural Networks? ([n. d.]). Ziwei Chai Siqi You Yang Yang Shiliang Pu Jiarong Xu Haoyang Cai and Weihao Jiang. [n. d.]. Can Abnormality be Detected by Graph Neural Networks? ([n. d.]).

4. Deep Anomaly Detection on Attributed Networks

5. Jingcan Duan , Siwei Wang , Xinwang Liu , Haifang Zhou , Jingtao Hu , and Hu Jin . 2022 . GADMSL: Graph Anomaly Detection on Attributed Networks via Multi-scale Substructure Learning. arXiv preprint arXiv:2211.15255 (2022). Jingcan Duan, Siwei Wang, Xinwang Liu, Haifang Zhou, Jingtao Hu, and Hu Jin. 2022. GADMSL: Graph Anomaly Detection on Attributed Networks via Multi-scale Substructure Learning. arXiv preprint arXiv:2211.15255 (2022).

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Community-Guided Contrastive Learning with Anomaly-Aware Reconstruction for Anomaly Detection on Attributed Networks;Lecture Notes in Computer Science;2024