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Found 3 papers, 3 papers with code
Personalized Federated Learning With Graph
We propose a novel structured federated learning (SFL) framework to learn both the global and personalized models simultaneously using client-wise relation graphs and clients' private data.
DAGCN: Dual Attention Graph Convolutional Networks
In this paper, we propose a novel framework called, dual attention graph convolutional networks (DAGCN) to address these problems.
Ranked #25 on
Graph Classification
on NCI1
A Comprehensive Survey on Graph Neural Networks
In this survey, we provide a comprehensive overview of graph neural networks (GNNs) in data mining and machine learning fields.
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