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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:

Anomaly Detection for Time Series Using VAE-LSTM Hybrid Model
Shu‐Yu Lin, Ronald Clark, Robert Birke, et al.
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2020), pp. 4322-4326
Closed Access | Times Cited: 169

Showing 1-25 of 169 citing articles:

Deep learning for anomaly detection in multivariate time series: Approaches, applications, and challenges
Gen Li, Jason J. Jung
Information Fusion (2022) Vol. 91, pp. 93-102
Closed Access | Times Cited: 146
Detecting cyberattacks using anomaly detection in industrial control systems: A Federated Learning approach
Trương Thu Hương, Ta Phuong Bac, Dao Minh Long, et al.
Computers in Industry (2021) Vol. 132, pp. 103509-103509
Open Access | Times Cited: 123
Unsupervised anomaly detection with LSTM autoencoders using statistical data-filtering
Sepehr Maleki, Sasan Maleki, Nicholas R. Jennings
Applied Soft Computing (2021) Vol. 108, pp. 107443-107443
Closed Access | Times Cited: 116
LSTM-Autoencoder-Based Anomaly Detection for Indoor Air Quality Time-Series Data
Yuanyuan Wei, Julian Jang‐Jaccard, Wen Xu, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 4, pp. 3787-3800
Open Access | Times Cited: 106
Variational transformer-based anomaly detection approach for multivariate time series
Xixuan Wang, Dechang Pi, Xiangyan Zhang, et al.
Measurement (2022) Vol. 191, pp. 110791-110791
Closed Access | Times Cited: 79
A novel orthogonal self-attentive variational autoencoder method for interpretable chemical process fault detection and identification
Xiaotian Bi, Jinsong Zhao
Process Safety and Environmental Protection (2021) Vol. 156, pp. 581-597
Closed Access | Times Cited: 73
openGauss
Guoliang Li, Xuanhe Zhou, Ji Sun, et al.
Proceedings of the VLDB Endowment (2021) Vol. 14, Iss. 12, pp. 3028-3042
Closed Access | Times Cited: 61
Satellite Telemetry Data Anomaly Detection Using Causal Network and Feature-Attention-Based LSTM
Zefan Zeng, Guang Jin, Chi Xu, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-21
Closed Access | Times Cited: 57
Do deep neural networks contribute to multivariate time series anomaly detection?
Julien Audibert, Pietro Michiardi, Frédéric Guyard, et al.
Pattern Recognition (2022) Vol. 132, pp. 108945-108945
Open Access | Times Cited: 42
Robust unsupervised network intrusion detection with self-supervised masked context reconstruction
Wei Wang, Songlei Jian, Yusong Tan, et al.
Computers & Security (2023) Vol. 128, pp. 103131-103131
Closed Access | Times Cited: 27
Anomaly Detection Method for Multivariate Time Series Data of Oil and Gas Stations Based on Digital Twin and MTAD-GAN
Yuanfeng Lian, Yueyao Geng, Tian Tian
Applied Sciences (2023) Vol. 13, Iss. 3, pp. 1891-1891
Open Access | Times Cited: 25
Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design
Hugo Wai Leung Mak, Runze Han, Hoover H. F. Yin
(2023)
Open Access | Times Cited: 20
A survey of unmanned aerial vehicle flight data anomaly detection: Technologies, applications, and future directions
Lei Yang, Shaobo Li, Chuanjiang Li, et al.
Science China Technological Sciences (2023) Vol. 66, Iss. 4, pp. 901-919
Closed Access | Times Cited: 20
Unsupervised Deep Learning for IoT Time Series
Ya Liu, Yingjie Zhou, Kai Yang, et al.
IEEE Internet of Things Journal (2023) Vol. 10, Iss. 16, pp. 14285-14306
Open Access | Times Cited: 19
Anomaly detection using a model-agnostic meta-learning-based variational auto-encoder for facility management
Jaeuk Moon, Yoona Noh, Seungwon Jung, et al.
Journal of Building Engineering (2023) Vol. 68, pp. 106099-106099
Closed Access | Times Cited: 18
Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design
Hugo Wai Leung Mak, Runze Han, Hoover H. F. Yin
Sensors (2023) Vol. 23, Iss. 7, pp. 3457-3457
Open Access | Times Cited: 17
AI-Based Anomaly Detection Techniques for Structural Fault Diagnosis Using Low-Sampling-Rate Vibration Data
Yub Jung, Eun-Gyo Park, Seon-Ho Jeong, et al.
Aerospace (2024) Vol. 11, Iss. 7, pp. 509-509
Open Access | Times Cited: 6
A joint model for IT operation series prediction and anomaly detection
Run-Qing Chen, Guanghui Shi, Wan‐Lei Zhao, et al.
Neurocomputing (2021) Vol. 448, pp. 130-139
Open Access | Times Cited: 40
A Novel Multivariate Time-Series Anomaly Detection Approach Using an Unsupervised Deep Neural Network
Peihai Zhao, Xiaoyan Chang, Mimi Wang
IEEE Access (2021) Vol. 9, pp. 109025-109041
Open Access | Times Cited: 35
Stgat-Mad : Spatial-Temporal Graph Attention Network For Multivariate Time Series Anomaly Detection
Jun Zhan, Siqi Wang, Xiandong Ma, et al.
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2022), pp. 3568-3572
Open Access | Times Cited: 25
Radio fingerprinting for anomaly detection using federated learning in LoRa-enabled Industrial Internet of Things
Subir Halder, Thomas Newe
Future Generation Computer Systems (2023) Vol. 143, pp. 322-336
Open Access | Times Cited: 13
A Multihead Attention Self-Supervised Representation Model for Industrial Sensors Anomaly Detection
Yiqun Qiao, Jinhu Lü, Tian Wang, et al.
IEEE Transactions on Industrial Informatics (2023) Vol. 20, Iss. 2, pp. 2190-2199
Closed Access | Times Cited: 13
Graph-guided masked autoencoder for process anomaly detection
Mingwei Jia, Danya Xu, Tao Yang, et al.
Process Safety and Environmental Protection (2024) Vol. 186, pp. 1345-1357
Closed Access | Times Cited: 5
The VAE-FastGA anomaly detection model based on subspace and weakly correlated ultra-high-dimensional data
Jiao Wan, Yanping Chen, Cong Gao
The Journal of Supercomputing (2025) Vol. 81, Iss. 3
Closed Access
A Multi-Scale Self-Supervision Approach for Bearing Anomaly Detection Using Sensor Data Under Multiple Operating Conditions
Zhuoheng Dai, Lei Jiang, Feifan Li, et al.
Sensors (2025) Vol. 25, Iss. 4, pp. 1185-1185
Open Access
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