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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:

Refining one-class representation: A unified transformer for unsupervised time-series anomaly detection
Guoxiang Zhong, Fagui Liu, Jun Jiang, et al.
Information Sciences (2023) Vol. 656, pp. 119914-119914
Closed Access | Times Cited: 11

Showing 11 citing articles:

A roadmap to fault diagnosis of industrial machines via machine learning: A brief review
Govind Vashishtha, Sumika Chauhan, Mert Sehri, et al.
Measurement (2024) Vol. 242, pp. 116216-116216
Closed Access | Times Cited: 11
Gdcmad: Graph-Based Dual-Contrastive Representation Learning for Multivariate Time Series Anomaly Detection
Sheng He, Wenxuan He, Mingjing Du, et al.
(2025)
Closed Access
Frequency-enhanced and decomposed transformer for multivariate time series anomaly detection
Shijiang Li, Zhihai Wang, Xiaokang Wang, et al.
Applied Intelligence (2025) Vol. 55, Iss. 6
Closed Access
TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection
Mengxuan Li, Ke Liu, Hongyang Chen, et al.
(2025), pp. 671-682
Closed Access
Rectifying inaccurate unsupervised learning for robust time series anomaly detection
Zejian Chen, Zuoyong Li, Xinwei Chen, et al.
Information Sciences (2024) Vol. 662, pp. 120222-120222
Closed Access | Times Cited: 3
Graph Attention Network and Informer for Multivariate Time Series Anomaly Detection
Mengmeng Zhao, Haipeng Peng, Lixiang Li, et al.
Sensors (2024) Vol. 24, Iss. 5, pp. 1522-1522
Open Access | Times Cited: 3
Detecting Cloud Anomaly via Broad Network-Based Contrastive Autoencoder
Guoxiang Zhong, Fagui Liu, Jun Jiang, et al.
IEEE Transactions on Network and Service Management (2024) Vol. 21, Iss. 3, pp. 3249-3263
Closed Access | Times Cited: 1
Anomaly Detectionin Network Traffic Scenarios by Resampling and Majority Voting with Concept Drift: A Hybrid Approach
Richa Singh, Nidhi Srivastava, Ashwani Kumar
2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) (2024), pp. 1-7
Closed Access
Graph-Augmented Contrastive Clustering for Time Series Data
Qin Zhang, Zhuoluo Liang, Alladoumbaye Ngueilbaye, et al.
(2024)
Closed Access
Towards accurate anomaly detection for cloud system via graph-enhanced contrastive learning
Zhen Zhang, Zhe Zhu, Xu Chen, et al.
Complex & Intelligent Systems (2024) Vol. 11, Iss. 1
Open Access
MLP-Mixer based Masked Autoencoders are Effective, Explainable and Robust for Time Series Anomaly Detection
Qideng Tang, Chaofan Dai, Yahui Wu, et al.
Proceedings of the VLDB Endowment (2024) Vol. 18, Iss. 3, pp. 798-811
Closed Access
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