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:
FederatedNILM: A Distributed and Privacy-Preserving Framework for Non-Intrusive Load Monitoring Based on Federated Deep Learning
Shuang Dai, Fanlin Meng, Qian Wang, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2023), pp. 01-08
Open Access | Times Cited: 7
Shuang Dai, Fanlin Meng, Qian Wang, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2023), pp. 01-08
Open Access | Times Cited: 7
Showing 7 citing articles:
Exploring the role of energy Communities: A comprehensive review
Muhammad Amin, Renato Procopio, Marco Invernizzi, et al.
Energy Conversion and Management X (2025), pp. 100883-100883
Open Access
Muhammad Amin, Renato Procopio, Marco Invernizzi, et al.
Energy Conversion and Management X (2025), pp. 100883-100883
Open Access
PCIR: Privacy‐Preserving Convolutional Neural Network Inference With Rapid Responsiveness
Jinguo Li, Yan Yan, Kai Zhang, et al.
Computational Intelligence (2025) Vol. 41, Iss. 2
Closed Access
Jinguo Li, Yan Yan, Kai Zhang, et al.
Computational Intelligence (2025) Vol. 41, Iss. 2
Closed Access
A Robust and Privacy-Aware Federated Learning Framework for Non-Intrusive Load Monitoring
Vidushi Agarwal, Omid Ardakanian, Sujata Pal
IEEE Transactions on Sustainable Computing (2024) Vol. 9, Iss. 5, pp. 766-777
Closed Access | Times Cited: 4
Vidushi Agarwal, Omid Ardakanian, Sujata Pal
IEEE Transactions on Sustainable Computing (2024) Vol. 9, Iss. 5, pp. 766-777
Closed Access | Times Cited: 4
Advancing Power System Services With Privacy-Preserving Federated Learning Techniques: A Review
Ran Zheng, Andreas Sumper, Mònica Aragüés‐Peñalba, et al.
IEEE Access (2024) Vol. 12, pp. 76753-76780
Open Access | Times Cited: 4
Ran Zheng, Andreas Sumper, Mònica Aragüés‐Peñalba, et al.
IEEE Access (2024) Vol. 12, pp. 76753-76780
Open Access | Times Cited: 4
Neural Load Disaggregation: Meta-Analysis, Federated Learning and Beyond
Hafsa Bousbiat, Yassine Himeur, Iraklis Varlamis, et al.
Energies (2023) Vol. 16, Iss. 2, pp. 991-991
Open Access | Times Cited: 12
Hafsa Bousbiat, Yassine Himeur, Iraklis Varlamis, et al.
Energies (2023) Vol. 16, Iss. 2, pp. 991-991
Open Access | Times Cited: 12
FPCNN: A fast privacy-preserving outsourced convolutional neural network with low-bandwidth
Jinguo Li, Yan Yan, Kai Zhang, et al.
Knowledge-Based Systems (2023) Vol. 283, pp. 111181-111181
Closed Access | Times Cited: 4
Jinguo Li, Yan Yan, Kai Zhang, et al.
Knowledge-Based Systems (2023) Vol. 283, pp. 111181-111181
Closed Access | Times Cited: 4
Semi-Federated Learning Based on Autoencoder for Non-Intrusive Load Monitoring
Chongyu Bao, Haitao Zhao, Ruize Li, et al.
(2023), pp. 1069-1073
Closed Access
Chongyu Bao, Haitao Zhao, Ruize Li, et al.
(2023), pp. 1069-1073
Closed Access
