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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:

Federated Meta-Learning for Fraudulent Credit Card Detection
Wenbo Zheng, Lan Yan, Chao Gou, et al.
(2020), pp. 4654-4660
Open Access | Times Cited: 75

Showing 1-25 of 75 citing articles:

A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
Qinbin Li, Zeyi Wen, Zhaomin Wu, et al.
IEEE Transactions on Knowledge and Data Engineering (2021) Vol. 35, Iss. 4, pp. 3347-3366
Open Access | Times Cited: 660
Intelligent financial fraud detection practices in post-pandemic era
Xiaoqian Zhu, Xiang Ao, Zidi Qin, et al.
The Innovation (2021) Vol. 2, Iss. 4, pp. 100176-100176
Open Access | Times Cited: 120
Recent advances on federated learning: A systematic survey
Bingyan Liu, Nuoyan Lv, Yuanchun Guo, et al.
Neurocomputing (2024) Vol. 597, pp. 128019-128019
Open Access | Times Cited: 27
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
Qinbin Li, Zeyi Wen, Zhaomin Wu, et al.
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 96
Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features
Xinyi Shang, Yang Lu, Gang Huang, et al.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (2022), pp. 2218-2224
Open Access | Times Cited: 42
DFML: Dynamic Federated Meta-Learning for Rare Disease Prediction
Bingyang Chen, Tao Chen, Xingjie Zeng, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2023) Vol. 21, Iss. 4, pp. 880-889
Closed Access | Times Cited: 17
Federated Learning for Credit Risk Assessment
Marc Goutier, Christopher Diebel, Martin Adam, et al.
Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences (2024)
Open Access | Times Cited: 7
Privacy-preserving federated learning framework in multimedia courses recommendation
Yangjie Qin, Ming Li, Jia Zhu
Wireless Networks (2022) Vol. 29, Iss. 4, pp. 1535-1544
Closed Access | Times Cited: 25
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity
Nannan Wu, Li Yu, Xuefeng Jiang, et al.
(2023), pp. 4424-4432
Open Access | Times Cited: 14
Human-Centered Recommender Systems
Miguel Portaz, Ángeles Manjarrés Riesco, Olga C. Santos
Human-computer interaction series (2025), pp. 593-617
Closed Access
Adaptive Clustered Federated Learning for Heterogeneous Data in Edge Computing
Biyao Gong, Tianzhang Xing, Zhidan Liu, et al.
Mobile Networks and Applications (2022) Vol. 27, Iss. 4, pp. 1520-1530
Closed Access | Times Cited: 21
Towards federated learning: An overview of methods and applications
Paula Raissa Silva, João Vinagre, João Gama
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2023) Vol. 13, Iss. 2
Closed Access | Times Cited: 12
Synergetic Focal Loss for Imbalanced Classification in Federated XGBoost
Jiao Tian, Pei‐Wei Tsai, Kai Zhang, et al.
IEEE Transactions on Artificial Intelligence (2023) Vol. 5, Iss. 2, pp. 647-660
Closed Access | Times Cited: 11
Efficiency of Federated Learning and Blockchain in Preserving Privacy and Enhancing the Performance of Credit Card Fraud Detection (CCFD) Systems
Tahani Baabdullah, Amani Alzahrani, Danda B. Rawat, et al.
Future Internet (2024) Vol. 16, Iss. 6, pp. 196-196
Open Access | Times Cited: 4
Blockchain-Based Federated Learning: A Survey and New Perspectives
Wanshan Ning, Y. Zhu, Caixia Song, et al.
Applied Sciences (2024) Vol. 14, Iss. 20, pp. 9459-9459
Open Access | Times Cited: 4
Defense Scheme of Federated Learning Based on GAN
Qing Zhang, Ping Zhang, Wenlong Lu, et al.
Electronics (2025) Vol. 14, Iss. 3, pp. 406-406
Open Access
A Federated Learning Algorithm with Adaptive Learning Rate
桁颍 朱
Advances in Applied Mathematics (2025) Vol. 14, Iss. 04, pp. 100-110
Closed Access
Privacy-Preserving Few-Shot Traffic Detection Against Advanced Persistent Threats via Federated Meta Learning
Y.-Q. Hu, Jun Wu, Gaolei Li, et al.
IEEE Transactions on Network Science and Engineering (2023) Vol. 11, Iss. 3, pp. 2549-2560
Closed Access | Times Cited: 10
A Review of Federated Meta-Learning and Its Application in Cyberspace Security
Fengchun Liu, Meng Li, Xiaoxiao Liu, et al.
Electronics (2023) Vol. 12, Iss. 15, pp. 3295-3295
Open Access | Times Cited: 9
Federated Learning-Based Credit Card Fraud Detection: Performance Analysis with Sampling Methods and Deep Learning Algorithms
Nahid Ferdous Aurna, Md Delwar Hossain, Yuzo Taenaka, et al.
(2023), pp. 180-186
Closed Access | Times Cited: 9
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning
Shaoxiong Ji, Yue Tan, Teemu Saravirta, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 9
Federated Learning with Personalized Local Differential Privacy
Ge Yang, Shaowei Wang, Haijie Wang
2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS) (2021)
Closed Access | Times Cited: 22
Towards a Federated Fuzzy Learning System
Anna Wilbik, Paul Grefen
2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (2021), pp. 1-6
Open Access | Times Cited: 19
A Review of Solving Non-IID Data in Federated Learning: Current Status and Future Directions
Wenhai Lu, Jieren Cheng, Xiulai Li, et al.
Communications in computer and information science (2024), pp. 58-72
Closed Access | Times Cited: 2
FedGAT-DCNN: Advanced Credit Card Fraud Detection Using Federated Learning, Graph Attention Networks, and Dilated Convolutions
Mengqiu Li, John Walsh
Electronics (2024) Vol. 13, Iss. 16, pp. 3169-3169
Open Access | Times Cited: 2
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