SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
时间: 2024-02-14 12:34:57 浏览: 30
"SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS"是一篇论文,提出了一种可扩展的图卷积实现方法,用于对具有图结构数据的半监督学习。该方法使用谱图卷积的一阶近似来确定卷积网络结构,并通过隐藏层的学习来编码图的局部结构特征和节点特征。这篇论文的作者是Thomas N. Kipf。\[1\]\[2\]\[3\]
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- *1* [GCN经典论文笔记:Semi-Supervised Classification with Graph Convolutional Networks](https://blog.csdn.net/qq_44624316/article/details/124664448)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^insert_down28v1,239^v3^insert_chatgpt"}} ] [.reference_item]
- *2* *3* [GCN(图卷积神经网络)的简单理解](https://blog.csdn.net/ziqingnian/article/details/109527842)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^insert_down28v1,239^v3^insert_chatgpt"}} ] [.reference_item]
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