Architectural Implications of Graph Neural Networks

Architectural Implications of Graph Neural Networks
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图神经网络的架构含义

DOI:
10.1109/lca.2020.2988991
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发表时间:
2020-01
影响因子:
2.3
通讯作者:
Guo Minyi
Guo Minyi
中科院分区:
计算机科学3区
文献类型:
--
作者:
Zhang Zhihui;Leng Jingwen;Ma Lingxiao;Miao Youshan;Li Chao;Guo Minyi

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图神经网络(GNN)代表了一种新兴的在图结构上运行的深度学习模型。由于其在许多图形相关任务中实现的高精度,它变得越来越受欢迎。然而,GNN 并没有得到很好的理解
Graph neural networks (GNN) represent an emerging line of deep learning models that operate on graph structures. It is becoming more and more popular due to its high accuracy achieved in many graph-related tasks. However, GNN is not as well understood in
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