Graph Isomorphism Network
Paper : GRAPH ISOMORPHISM NETWORK Code : 摘要 作者使用Weisfeiler-Lehman(WL) test 和同構圖判定問題來評估GNN網絡的表達能力，並提出了GIN網絡結構，理論分析GIN的表達能力優於GraphSAGE GCN等結構，在多任務上準確率達到了SOTA。WL測試與GNN具有相似的信息傳遞方式，在WL test算法運行的過程中，算法構造了從
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相關文章
- 1. Graph Attention Network
- 2. Graph Neural Network Review
- 3. Learning about Graph Network
- 4. CS224W 18.1-Limitations of Graph Neural Network
- 5. 《A (Sub)Graph Isomorphism Algorithm for Matching Large Graphs》論文總結
- 6. (Network Analysis)graph centrality measures
- 7. CS224W 8.2-Graph Neural Network
- 8. Cs224W 8.1-Graph Neural Network
- 9. Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph
- 10. Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation