Machine learning
图神经网络
图神经网络（GNN）是一种深度学习方法，由Kipf和Welling在2017年通过图卷积网络（Graph Convolutional Network）推广开来，它从由节点和边组成的网络（图）结构中的关系中学习。它适用于自然关系型数据，如社交网络、分子结构和推荐系统。
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
Method map
The neighbourhood of related methods — select a node to explore.
来源
- Kipf, T.N. & Welling, M. (2017). Semi-Supervised Classification with Graph Convolutional Networks. ICLR. link ↗
- Veličković, P. et al. (2018). Graph Attention Networks. ICLR. link ↗
- Hamilton, W.L. (2020). Graph Representation Learning. Morgan & Claypool. DOI: 10.1007/978-3-031-01588-5 ↗
如何引用本页
ScholarGate. (2026, June 1). Graph Neural Network (GNN). ScholarGate. https://scholargate.app/zh/deep-learning/gnn
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
Compare side by side →