论文笔记——Permutohedral-GCN: Graph Convolutional Networks with Global Attention

时间 2020-12-23

标签深度学习神经网络机器学习繁體版

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【论文笔记】Permutohedral-GCN: Graph Convolutional Networks with Global Attention 作者：HeshamMostafa，MarcelNassar 代码：无摘要图卷积网络（GCNs）通过聚集图中邻居节点的特征来更新节点的特征向量。这会忽略来自遥远节点的潜在有用贡献。本文引入了一种全局注意力机制，其中一个节点可以有选择地关注并聚合图

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1. GRAPH ATTENTION NETWORKS论文笔记
2. Efficient Graph Generation with Graph Recurrent Attention Networks--NIPS2019--论文笔记
3. 论文笔记：LCML 2019 Simplifying Graph Convolutional Networks
4. 论文笔记：Multi-Label Image Recognition with Graph Convolutional Networks
5. GRAPH ATTENTION NETWORKS--论文阅读笔记
6. 论文笔记之Graph Attention Networks
7. 论文笔记《Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting》
8. GRAPH ATTENTION NETWORKS笔记
9. Multi-Label Image Recognition with Graph Convolutional Networks 论文笔记
10. Multi-Label Image Recognition with Graph Convolutional Networks 论文阅读笔记

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