【論文閱讀-HGP-SL】Hierarchical Graph Pooling with Structure Learning
論文地址：https://arxiv.org/pdf/1911.05954 代碼地址：https://github.com/cszhangzhen/HGP-SL 來源：WWW 2020 這篇論文提出了一種新的基於TopK的圖池化操作符HGP-SL，它可以集成到各種圖神經網絡架構中。HGP-SL將圖池和結構學習整合到一個統一的模塊中，以生成圖的層次表示。更具體地說，圖池操作自適應地選擇節點的子集，形
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相關文章
- 1. 圖分類《Hierarchical Graph Representation Learning with Differentiable Pooling》閱讀筆記
- 2. 13.Hierarchical Graph Representation Learning with Differentiable Pooling
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- 4. 《論文閱讀》Fine-Grained Video-Text Retrieval With Hierarchical Graph Reasoning
- 5. [DIFFPOOL] - Hierarchical Graph Representation Learning with Differentiable Pooling 圖分類 NeurIPS 2018
- 6. [DIFFPOOL 圖分類] - Hierarchical Graph Representation Learning with Differentiable Pooling NeurIPS 2018
- 7. 論文閱讀 (十九)：Deep Multi-instance Learning with Dynamic Pooling (2018DP-MINN)
- 8. 《Deep Learning of Graph Matching》論文閱讀
- 9. 閱讀論文 GraphGAN: Graph Representation Learning with Generative Adversarial Nets
- 10. 論文閱讀筆記《Few-Shot Learning with Graph Neural Networks》