GNN Pooling(十一)：Edge Contraction Pooling for Graph Neural Networks，2019
本文的作者來自An-Institut Technische Universität München，本文至今好像還未正式發表。 本文提出了EdgePool，其能夠學習一個局部和稀疏的硬池變換，並自然地考慮到圖結構，確保不會完全刪除節點。EdgePool優於其他的池化方法，可以很容易地集成到大多數GNN模型中，並且在節點分類和圖分類方面都提高了性能。 EdgePool Edge contractio
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相關文章
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