论文笔记：LCML 2020 Simple and Deep Graph Convolutional Networks
前言 图卷积网络(GCNs)是一种针对图结构数据的强大的深度学习方法。最近，GCNs和后续的变体在实际数据集中的各种应用领域显示了优越的性能。大多数目前的GCN模型是浅层结构的，由于过度平滑的问题。本文研究了深度图卷积网络的设计与分析问题，提出了GCNII，它是普通GCN模型的扩展，具有两种简单而有效的技术:初始残差和恒等映射。这两种技术有效地缓解了过度平滑的问题。实验表明，深层GCNII模型在各
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相关文章
- 1. 论文笔记：LCML 2019 Simplifying Graph Convolutional Networks
- 2. 《Simple and Deep Graph Convolutional Networks》--论文阅读笔记
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