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:

GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction
Amit Roy, Juan Shu, Jia Li, et al.
(2024)
Open Access | Times Cited: 10

Showing 10 citing articles:

Enhancing Recommender Systems with Anomaly Detection: A Graph Neural Network Approach
Bahareh Rahmatikargar, Pooya Moradian Zadeh, Ziad Kobti
Studies in computational intelligence (2025), pp. 16-28
Closed Access

Graph anomaly detection based on hybrid node representation learning
Xiang Wang, Hao Dou, Dibo Dong, et al.
Neural Networks (2025) Vol. 185, pp. 107169-107169
Closed Access

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

Graph Anomaly Detection via Diffusion Enhanced Multi-View Contrastive Learning
Xiangjie Kong, Jin Liu, Huan Li, et al.
Knowledge-Based Systems (2025), pp. 113093-113093
Closed Access

DBAD: Dual branch reconstruction for industrial anomaly detection
Huaze Cai, Shuaishi Liu
Electronics Letters (2024) Vol. 60, Iss. 15
Open Access | Times Cited: 1

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

Fiber Optical Module Anomaly Detection Using Graph Deep Learning Model
Yunjie Li, Jhao-Yin Li, Hao-Yu Kao, et al.
(2024), pp. 1-5
Closed Access

Simultaneously Detecting Node and Edge Level Anomalies on Heterogeneous Attributed Graphs
Rizal Fathony, Jenn Ng, Jia Chen
2022 International Joint Conference on Neural Networks (IJCNN) (2024), pp. 1-10
Closed Access

A Structural Information Guided Hierarchical Reconstruction for Graph Anomaly Detection
Dongcheng Zou, Hao Peng, Chunyang Liu
(2024), pp. 4318-4323
Closed Access

VQ-VGAE: Vector Quantized Variational Graph Auto-Encoder for Unsupervised Anomaly Detection
Tarek Seghair, Olfa Besbes, Takoua Abdellatif, et al.
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 2370-2375
Closed Access

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