Quantifying the non-isomorphism of global urban road networks using GNNs and graph kernels
Abstract A novel concept of quantifying graph non-isomorphism is introduced to measure structural differences between graphs, and thus overcoming the strict limitations of traditional graph isomorphism tests. This paper trains Graph Neural Networks (GNNs) and graph kernels to classify urban road net...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-90839-x |