Graph neural networks for network analysis
<p>With an increasing number of applications where data can be represented as graphs, graph neural networks (GNNs) are a useful tool to apply deep learning to graph data. Signed and directed networks are important forms of networks that are linked to many real-world problems, such as ranking f...
主要作者: | He, Y |
---|---|
其他作者: | Dong, X |
格式: | Thesis |
语言: | English |
出版: |
2024
|
主题: |
相似书籍
-
JGNN: Graph Neural Networks on native Java
由: Emmanouil Krasanakis, et al.
出版: (2023-07-01) -
Auto-GNN: Neural architecture search of graph neural networks
由: Kaixiong Zhou, et al.
出版: (2022-11-01) -
FloodGNN-GRU: a spatio-temporal graph neural network for flood prediction
由: Arnold Kazadi, et al.
出版: (2024-01-01) -
Graph neural networks with a distribution of parametrized graphs
由: Lee, See Hian, et al.
出版: (2024) -
p2pGNN: A Decentralized Graph Neural Network for Node Classification in Peer-to-Peer Networks
由: Emmanouil Krasanakis, et al.
出版: (2022-01-01)