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Dec, 2023
GNN社群检测中评估不确定性:随机性量化措施比较
Uncertainty in GNN Learning Evaluations: A Comparison Between Measures for Quantifying Randomness in GNN Community Detection
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William Leeney, Ryan McConville
TL;DR
Graph Neural Networks在无监督社区检测中的增强能力归因于它们能够编码图的连通性和特征信息空间,该研究讨论了性能基准、超参数优化和随机性对结果的一致性和质量的影响。
Abstract
(1) The enhanced capability of
graph neural networks
(GNNs) in
unsupervised community detection
of clustered nodes is attributed to their capacity to encode both the connectivity and feature information spaces of
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