论文笔记：Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks 1、四个问题 要解决什么问题？ 半监督任务。给定一个图，其中一部节点已知标签，剩下的未知，要对整个图上的节点进行分类。 用了什么方法解决？ 提出了一种卷积神经网络的变种，即提出了一种新的图卷积方法。 使用谱图卷积（spectral graph convolution）的
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相关文章
- 1. Semi-Supervised Classification With Graph Convolutional Networks
- 2. SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 3. Semi-Supervised Classification with Graph Convolutional Networks
- 4. 【GCN】论文笔记：SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 5. 论文笔记之：Semi-supervised Classification with Graph Convolutional Networks
- 6. 论文笔记：SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 7. 论文笔记：LCML 2019 Simplifying Graph Convolutional Networks
- 8. 论文阅读笔记：GAS---spam review detection with graph convolutional networks
- 9. 翻译--SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 10. Graph Convolutional Networks for Text Classification阅读笔记