GNN Pooling(一)：Graph U-Nets，ICML2019
本文的两位作者都来自TexasA&M University, TX, USA。看起来有些熟悉，果然是咱们之前读过的论文的作者：Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations，WWW。并且，在池化过程中采用的基本思路是都差不都的。 相比于图卷积的研究，针对于图池化的研究要少许多。本
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相关文章
- 1. ICML2019 Self-Attention Graph Pooling
- 2. GNN中的Graph Pooling
- 3. GNN Pooling(十一)：Edge Contraction Pooling for Graph Neural Networks，2019
- 4. GNN Pooling(九)：Structure-Feature based Graph Self-adaptive Pooling，WWW2020
- 5. Hierarchical Graph Representation Learning with Differentiable Pooling摘要
- 6. 13.Hierarchical Graph Representation Learning with Differentiable Pooling
- 7. Graph Neural Networks (GNN)（三）：Spectral-GNN 之 GCN
- 8. Graph Neural Network（GNN）概述
- 9. GNN Pooling(三)：An End-to-End Deep Learning Architecture for Graph Classification，AAAI2018；以及图核
- 10. 图神经网络论文阅读(十九) Position-aware Graph Neural Networks，ICML2019