GNN Pooling(九)：Structure-Feature based Graph Self-adaptive Pooling，WWW2020
目录 PROPOSED METHODS 实验 文本一共有…九个作者，分别来自西安电子科技大学，Shanghai BNC，Murdoch University以及University of Western Australia。 本文提出了一种新的图自适应池化方法（ GSAPool），其目的如下:(1)构建合理的池化图拓扑，同时考虑了图的结构和特征信息，在节点选择上提供了更高的准确性和客观性;(2)使
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相关文章
- 1. GNN中的Graph Pooling
- 2. GNN Pooling(一)：Graph U-Nets，ICML2019
- 3. ICML2019 Self-Attention Graph Pooling
- 4. GNN Pooling(十一)：Edge Contraction Pooling for Graph Neural Networks，2019
- 5. Hierarchical Graph Representation Learning with Differentiable Pooling摘要
- 6. 13.Hierarchical Graph Representation Learning with Differentiable Pooling
- 7. 【Bilinear Pooling】《A Novel DR Classfication Scheme based on Compact Bilinear Pooling CNN and GBDT》
- 8. 池化Pooling中的Max Pooling
- 9. Roi pooling,Roi Align,Precise Roi pooling
- 10. 【ROI Pooling】Region of interest pooling