《Predict then Propagate: Graph Neural Networks meet Personalized PageRank》论文阅读笔记

时间 2021-01-02

标签论文阅读总结 PPNP APPNP PageRank 卷积神经网络GCN 消息传递繁體版

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文章：Predict then Propagate: Graph Neural Networks meet Personalized PageRank 出处：ICLR 2019 作者：Johannes Klicpera, Aleksandar Bojchevski & Stephan Gunnemann 机构：Technical University of Munich, Germany 1. 背

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1. PREDICT THEN PROPAGATE: GRAPH NEURAL NETWORKS MEET PERSONALIZED PAGERANK
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1. PREDICT THEN PROPAGATE: GRAPH NEURAL NETWORKS MEET PERSONALIZED PAGERANK
2. GRAPH ATTENTION NETWORKS--论文阅读笔记
3. 论文阅读笔记：Random Walk Graph Neural Networks（NIPS2020）
4. 论文阅读笔记《Few-Shot Learning with Graph Neural Networks》
5. Graph Neural Networks for User Identity Linkage 2019 论文阅读笔记
6. 论文阅读笔记A Comprehensive Survey on Graph Neural Networks
7. 论文：GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond 阅读笔记
8. 论文阅读 Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks
9. 【论文阅读笔记】Ristretto： Hardware-Oriented Approximation of Convolutional Neural Networks
10. 论文阅读笔记: Modeling Relational Data with Graph Convolutional Networks

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