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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:

VAE-Based Interpretable Latent Variable Model for Process Monitoring
Zhuofu Pan, Yalin Wang, Yue Cao, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 5, pp. 6075-6088
Closed Access | Times Cited: 12

Showing 12 citing articles:

EaLDL: Element-Aware Lifelong Dictionary Learning for Multimode Process Monitoring
Keke Huang, Hengxing Zhu, Dehao Wu, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 36, Iss. 2, pp. 3744-3757
Closed Access | Times Cited: 23
Data-Driven Process Monitoring and Fault Diagnosis: A Comprehensive Survey
Afrânio Melo, Maurício Melo Câmara, José Carlos Pinto
Processes (2024) Vol. 12, Iss. 2, pp. 251-251
Open Access | Times Cited: 11
Robust Attitude Tracking Control Based on Adaptive Dynamic Programming for Flexible Dumbbell-Shaped Spacecraft
Wenke Huang, Guangtao Ran, Bohui Wang, et al.
IEEE Transactions on Aerospace and Electronic Systems (2024) Vol. 60, Iss. 2, pp. 2394-2406
Closed Access | Times Cited: 4
Leveraging variational autoencoders and recurrent neural networks for demand forecasting in supply chain management: A case study
Khaoula Khlie, Zoubida Benmamoun, Widad Fethallah, et al.
Journal of Infrastructure Policy and Development (2024) Vol. 8, Iss. 8, pp. 6639-6639
Open Access | Times Cited: 4
Novel dynamic data-driven modeling based on feature enhancement with derivative memory LSTM for complex industrial process
Xiuli Zhu, Jiajun Xu, Zixuan Fu, et al.
Neurocomputing (2025), pp. 129619-129619
Closed Access
KalmanAE: Deep Embedding Optimized Kalman Filter for Time Series Anomaly Detection
Xunhua Huang, Fengbin Zhang, Ruidong Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 6
Margin-Maximized Hyperspace for Fault Detection and Prediction: A Case Study With an Elevator Door
Minjae Kim, Seho Son, Ki‐Yong Oh
IEEE Access (2023) Vol. 11, pp. 128580-128595
Open Access | Times Cited: 6
Process Monitoring for Covariance Matrixes with Latent Structures
Qing Zou, Li Jian, Dong Ding, et al.
IISE Transactions (2024), pp. 1-12
Closed Access | Times Cited: 1
A Spatial–Temporal Variational Graph Attention Autoencoder Using Interactive Information for Fault Detection in Complex Industrial Processes
Mingjie Lv, Yonggang Li, Huiping Liang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 3, pp. 3062-3076
Closed Access | Times Cited: 4
Distributed process monitoring based on Kantorovich distance-multiblock variational autoencoder and Bayesian inference
Zongyu Yao, Qingchao Jiang, Xingsheng Gu
Chinese Journal of Chemical Engineering (2024) Vol. 73, pp. 311-323
Closed Access
Deep Canonical Variate Analysis with Interpretable Attribute Guidance for Three-Phase Flow Process Monitoring
Linghan Li, Shumei Zhang, Feng Dong, et al.
2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) (2024), pp. 1-6
Closed Access
A new generative adversarial networks-based fault diagnosis framework: Learning a mapping to estimate fault
Ling Li, Zhuofu Pan, Yanyuan Ma, et al.
Neurocomputing (2024), pp. 129288-129288
Closed Access
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