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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Generative Adversarial Attributed Network Anomaly Detection
Zhenxing Chen, Bo Liu, Meiqing Wang, et al.
(2020)
Closed Access | Times Cited: 37

Showing 1-25 of 37 citing articles:

A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video
Mariana Iuliana Georgescu, Radu Tudor Ionescu, Fahad Shahbaz Khan, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2021), pp. 1-1
Open Access | Times Cited: 127
GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction
Amit Roy, Juan Shu, Jia Li, et al.
(2024)
Open Access | Times Cited: 14
ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection
Junwei He, Qianqian Xu, Yangbangyan Jiang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 8, pp. 8481-8489
Open Access | Times Cited: 8
Recognition of Yuan blue and white porcelain produced in Jingdezhen based on graph anomaly detection combining portable X-ray fluorescence spectrometry
Jinwei Li, Yifei Yang, Dongmian Zou, et al.
Heritage Science (2024) Vol. 12, Iss. 1
Open Access | Times Cited: 6
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective
Z. C. Zhang, Minhua Lin, Enyan Dai, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 4386-4397
Open Access | Times Cited: 6
Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges
Jing Ren, Feng Xia, Ivan Lee, et al.
ACM Transactions on Intelligent Systems and Technology (2022) Vol. 14, Iss. 2, pp. 1-29
Open Access | Times Cited: 25
Semi-supervised Anomaly Detection on Attributed Graphs
Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara
2022 International Joint Conference on Neural Networks (IJCNN) (2021), pp. 1-8
Open Access | Times Cited: 28
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs
Tian Sheng, Jihai Dong, Jintang Li, et al.
(2023), pp. 2306-2314
Open Access | Times Cited: 11
Adversarial Deep Learning for Network Anomaly Detection
T. Jyotsna, P. Deepika, R. Usha, et al.
Cognitive science and technology (2025), pp. 523-533
Closed Access
Enhancing Detection Accuracy and Security in Deep Learning
G. Surekha, T. Pratyusha, T. Jyotsna, et al.
Cognitive science and technology (2025), pp. 485-497
Closed Access
How to use Graph Data in the Wild to Help Graph Anomaly Detection?
Yuxuan Cao, Jiarong Xu, Chen Zhao, et al.
(2025), pp. 61-72
Closed Access
Higher-order Structure Based Anomaly Detection on Attributed Networks
Xu Yuan, N. Zhou, Shuo Yu, et al.
2021 IEEE International Conference on Big Data (Big Data) (2021)
Open Access | Times Cited: 26
Cross-Domain Graph Anomaly Detection via Anomaly-Aware Contrastive Alignment
Qizhou Wang, Guansong Pang, Mahsa Salehi, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 4, pp. 4676-4684
Open Access | Times Cited: 10
GRAM: An interpretable approach for graph anomaly detection using gradient attention maps
Yifei Yang, Peng Wang, Xiaofan He, et al.
Neural Networks (2024) Vol. 178, pp. 106463-106463
Open Access | Times Cited: 3
Hybrid-Order Anomaly Detection on Attributed Networks
Ling Huang, Ye Zhu, Yuefang Gao, et al.
IEEE Transactions on Knowledge and Data Engineering (2021) Vol. 35, Iss. 12, pp. 12249-12263
Closed Access | Times Cited: 22
Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection
Yuanchen Bei, Sheng Zhou, Qiaoyu Tan, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2023), pp. 11-20
Open Access | Times Cited: 7
Multi-label graph node classification with label attentive neighborhood convolution
Cangqi Zhou, Hui Chen, Jing Zhang, et al.
Expert Systems with Applications (2021) Vol. 180, pp. 115063-115063
Closed Access | Times Cited: 13
SWSSL: Sliding Window-Based Self-Supervised Learning for Anomaly Detection in High-Resolution Images
Haoyu Dong, Yifan Zhang, Hanxue Gu, et al.
IEEE Transactions on Medical Imaging (2023) Vol. 42, Iss. 12, pp. 3860-3870
Closed Access | Times Cited: 4
MetaGAD: Meta Representation Adaptation for Few-Shot Graph Anomaly Detection
Xiongxiao Xu, Kaize Ding, Canyu Chen, et al.
2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA) (2024), pp. 1-10
Open Access | Times Cited: 1
Interaction-Focused Anomaly Detection on Bipartite Node-and-Edge-Attributed Graphs
Rizal Fathony, Jenn Ng, Jia Chen
2022 International Joint Conference on Neural Networks (IJCNN) (2023), pp. 1-10
Closed Access | Times Cited: 3
Few-shot Message-Enhanced Contrastive Learning for Graph Anomaly Detection
Fan Xu, Nan Wang, Xuezhi Wen, et al.
(2023)
Open Access | Times Cited: 3
GLAD: Content-Aware Dynamic Graphs For Log Anomaly Detection
Yufei Li, Yanchi Liu, H. Wang, et al.
(2023), pp. 9-18
Open Access | Times Cited: 2
Degan - Decomposition-Based Unified Anomaly Detection in Static Networks
Ahmet Tüzen, Yusuf Yaslan
(2024)
Closed Access
A New Scheme for Abnormal Data Transmission Behavior Detection with Network-Wide Perspective
Weikang Xiao, Yi Xie
(2024), pp. 122-133
Closed Access
Graph Anomaly Detection with Domain-Agnostic Pre-Training and Few-Shot Adaptation
Xujia Li, Lei Chen
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2024), pp. 2667-2680
Closed Access
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