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May, 2024
关联性提升:通过图间关系推进图神经网络
Relating-Up: Advancing Graph Neural Networks through Inter-Graph Relationships
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Qi Zou, Na Yu, Daoliang Zhang, Wei Zhang, Rui Gao
TL;DR
通过引入Relating-Up模块,利用图之间的关系,增强了Graph Neural Networks的表达能力,使其能够更准确地包含更广泛的图关系,并且在16个基准数据集上的评估表明,将Relating-Up集成到GNN架构中显著提高了性能。
Abstract
graph neural networks
(
gnns
) have excelled in learning from graph-structured data, especially in understanding the relationships within a single graph, i.e., intra-graph relationships. Despite their successes,
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