SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS 摘要 文章呈现了一种可缩放的半监督学习方法，利用卷积神经网络变种来进行图结构数据的学习。通过spectral graph convolution（谱图卷积）的局部一阶近似来确定卷积网络结构。隐藏层的表示是通过编码局部图结构以及结点特征来进行。 介绍 作者主要贡献： 介绍
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相关文章
- 1. Semi-Supervised Classification With Graph Convolutional Networks
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