semi -supervised classification with graph convolutional networks學習必記
1 主要解決的問題 半監督學習：用於少量節點標籤未知，例如文本、citation network、知識圖譜分類 2 主要思想 採用圖卷積中的一階局部近似（即K=1），這部分的理解可以參考Chebyshev多項式作爲GCN卷積核 當K=1 時有兩個參數,模型scales linearly in the number of graph edges ,同時可以表徵局部圖結構和節點的特徵： 3. 半監度節
相關文章
- 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. 翻譯--SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 5. Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification
- 6. 論文筆記：Semi-Supervised Classification with Graph Convolutional Networks
- 7. 【GCN】論文筆記：SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 8. 論文筆記之：Semi-supervised Classification with Graph Convolutional Networks
- 9. 論文筆記：SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 10. 論文翻譯：圖卷積入門-SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 更多相關文章...
- • 您已經學習了 XML Schema，下一步學習什麼呢？ - XML Schema 教程
- • 我們已經學習了 SQL，下一步學習什麼呢？ - SQL 教程
- • Tomcat學習筆記（史上最全tomcat學習筆記）
- • 適用於PHP初學者的學習線路和建議
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
歡迎關注本站公眾號,獲取更多信息
相關文章
- 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. 翻譯--SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 5. Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification
- 6. 論文筆記：Semi-Supervised Classification with Graph Convolutional Networks
- 7. 【GCN】論文筆記：SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 8. 論文筆記之：Semi-supervised Classification with Graph Convolutional Networks
- 9. 論文筆記：SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
- 10. 論文翻譯：圖卷積入門-SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS