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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:

DAGAD: Data Augmentation for Graph Anomaly Detection
Fanzhen Liu, Xiaoxiao Ma, Jia Wu, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2022), pp. 259-268
Open Access | Times Cited: 24

Showing 24 citing articles:

Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation
Shuang Zhou, Xiao Huang, Ninghao Liu, et al.
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 35, Iss. 12, pp. 12721-12735
Open Access | Times Cited: 13
A comprehensive survey on GNN-based anomaly detection: taxonomy, methods, and the role of large language models
Ziqi Yuan, Qingyun Sun, Haoyi Zhou, et al.
International Journal of Machine Learning and Cybernetics (2025)
Closed Access
Mining Mobile Network Fraudsters with Augmented Graph Neural Networks
Xinxin Hu, Haotian Chen, Hongchang Chen, et al.
Entropy (2023) Vol. 25, Iss. 1, pp. 150-150
Open Access | Times Cited: 9
Towards Graph-level Anomaly Detection via Deep Evolutionary Mapping
Xiaoxiao Ma, Jia Wu, Jian Yang, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2023), pp. 1631-1642
Closed Access | Times Cited: 9
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
Anomaly Detection for Telemetry Time Series Using a Denoising Diffusion Probabilistic Model
Jialin Sui, Jinsong Yu, Yue Song, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 10, pp. 16429-16439
Closed Access | Times Cited: 2
Decoupling Anomaly Discrimination and Representation Learning: Self-supervised Learning for Anomaly Detection on Attributed Graph
Yanming Hu, Chuan Chen, BoWen Deng, et al.
Data Science and Engineering (2024) Vol. 9, Iss. 3, pp. 264-277
Open Access | Times Cited: 2
PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection
Junjun Pan, Yixin Liu, Yizhen Zheng, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2023), pp. 1253-1258
Open Access | Times Cited: 6
Knowledge Graph Enhanced Heterogeneous Graph Neural Network for Fake News Detection
Bingbing Xie, Xiaoxiao Ma, Jia Wu, et al.
IEEE Transactions on Consumer Electronics (2023) Vol. 70, Iss. 1, pp. 2826-2837
Closed Access | Times Cited: 5
Unsupervised Graph Outlier Detection: Problem Revisit, New Insight, and Superior Method
Yihong Huang, Liping Wang, Fan Zhang, et al.
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2023), pp. 2565-2578
Open Access | Times Cited: 4
FedKG: A Knowledge Distillation-Based Federated Graph Method for Social Bot Detection
Xiujuan Wang, Kangmiao Chen, Keke Wang, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3481-3481
Open Access | Times Cited: 1
Enhancing Intrusion Detection Through Data Perturbation Augmentation Strategy
Uneneibotejit Otokwala, Andrey V. Petrovskiy, Igor Kotenko
(2024), pp. 269-272
Closed Access | Times Cited: 1
LabelGen: An Anomaly Label Generative Framework for Enhanced Graph Anomaly Detection
Siqi Xia, Sutharshan Rajasegarar, Lei Pan, et al.
IEEE Access (2024) Vol. 12, pp. 121971-121982
Open Access | Times Cited: 1
Class Label-aware Graph Anomaly Detection
Junghoon Kim, Yeonjun In, Kanghoon Yoon, et al.
(2023)
Open Access | Times Cited: 3
A graph encoder–decoder network for unsupervised anomaly detection
Mahsa Mesgaran, A. Ben Hamza
Neural Computing and Applications (2023) Vol. 35, Iss. 32, pp. 23521-23535
Closed Access | Times Cited: 3
Graph Anomaly Detection with Graph Convolutional Networks
Aabid A. Mir, Megat F. Zuhairi, Shahrulniza Musa
International Journal of Advanced Computer Science and Applications (2023) Vol. 14, Iss. 11
Open Access | Times Cited: 3
Discriminative Graph-Level Anomaly Detection via Dual-Students-Teacher Model
Fu Lin, Xuexiong Luo, Jia Wu, et al.
Lecture notes in computer science (2023), pp. 261-276
Closed Access | Times Cited: 2
Design and Application of Consistent Balanced Fraud Detectors Based on Graph Neural Networks with Focal-Loss and Dice-Loss
Huilin Huang, Yongxi Fan, Da Zheng
(2024)
Closed Access
Product Anomaly Detection on Heterogeneous Graphs with Sparse Labels
Yin Dan, Sihang Fang, Tianshuo Wang, et al.
Lecture notes in computer science (2024), pp. 97-111
Closed Access
A Structural Information Guided Hierarchical Reconstruction for Graph Anomaly Detection
Dongcheng Zou, Hao Peng, Chunyang Liu
(2024), pp. 4318-4323
Closed Access
Graph Contrastive Learning for Internet Financial Fraud Detection
Xiaoguo Wang, Yuxiao Wang
(2024), pp. 153-157
Closed Access
Heterophilic Graph Invariant Learning for Out-of-Distribution of Fraud Detection
Lingfei Ren, Ruimin Hu, Zheng Wang, et al.
(2024), pp. 11032-11040
Closed Access
Location-Adaptive Generative Graph Augmentation for Fraud Detection
Lin Meng, Xiaonan Zhang, Jiawei Zhang, et al.
(2023), pp. 24-30
Closed Access
Unsupervised Graph Outlier Detection: Problem Revisit, New Insight, and Superior Method
Yihong Huang, Liping Wang, Fan Zhang, et al.
arXiv (Cornell University) (2022)
Open Access
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