English(EN) SynCo: Synthetic Community-Aware Attributed Graph Generator for Graph Neural Network Benchmarking

新的SynCo生成器增强了图神经网络基准测试

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-11 04:00

研究人员开发了SynCo，这是一种用于合成属性图的新型生成器，旨在改进图神经网络（GNN）的基准测试。与以往常常依赖不切实际的无标度网络假设的生成器不同，SynCo允许用户控制节点度分布和子社区结构。这种灵活性能够更准确地评估GNN在社区检测、图模仿和超参数调整等任务中的表现。SynCo在合成图生成和数据增强方面已展现出卓越的性能，能够生成多达210万个节点的图。 AI

影响通过提供更现实和可控的合成数据集，增强了图神经网络的基准测试和开发能力。

排序理由该集群包含一篇学术论文，详细介绍了一种用于GNN基准测试的合成图生成新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Guilherme Henrique Messias, Mariana Caravanti de Souza, Sylvia Iasulaitis, Alan Dem\'etrius Baria Valejo · 2026-09-11 04:00

SynCo：用于图神经网络基准测试的合成社区感知属性图生成器

arXiv:2609.10742v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) are powerful models for handling attributed graphs in tasks such as classification, link prediction, and community detection, as they enable the aggregation of information from both structural and sema…

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SynCo：用于图神经网络基准测试的合成社区感知属性图生成器

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