Work

HarmoFGL: Harmonizing GNN Latent Factors for Federated Graph Learning

Year: 2026

Type: article

Source: IEEE Transactions on Neural Networks and Learning Systems

DOI: 10.1109/tnnls.2025.3648828

Authors: Yeyu Yan, Zhenfeng Zhu, Shuai Zheng, Hongli Xu, Yawei Zhao, Kunlun He, Yao Zhao

Institutions: Beijing Jiaotong University, Chinese PLA General Hospital

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: National Natural Science Foundation of China, China Postdoctoral Science Foundation, Beijing Municipal Natural Science Foundation, National Key Research and Development Program of China

Awards: G1284323090, G449509765, G6640703287, G7019254261, G7716759923, G8002731450, G854619240

OpenAlex ID: W7118653003

FWCI: 7.415

Cites: 42

Cited by: 2

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