How does over-squashing affect the power of GNNs?
Graph Neural Networks (GNNs) are the state-of-the-art model for machine learning on graph-structured data. The most popular class of GNNs operate by exchanging information between adjacent nodes, and are known as Message Passing Neural Networks (MPNNs). While understanding the expressive power of MP...
| 主要な著者: | , , , , , , |
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| フォーマット: | Journal article |
| 言語: | English |
| 出版事項: |
Journal of Machine Learning Research
2024
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