An end-to-end attention-based approach for learning on graphs
Abstract There has been a recent surge in transformer-based architectures for learning on graphs, mainly motivated by attention as an effective learning mechanism and the desire to supersede the hand-crafted operators characteristic of message passing schemes. However, concerns over their empirical...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-06-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-60252-z |
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