Recurrent graph neural networks and their connections to bisimulation and logic
The success of Graph Neural Networks (GNNs) in practice has motivated extensive research on their theoretical properties. This includes recent results that characterise node classifiers expressible by GNNs in terms of first order logic. Most of the analysis, however, has been focused on GNNs with fi...
| Main Authors: | , , |
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| Format: | Conference item |
| Language: | English |
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AAAI Conference on Artificial Intelligence
2024
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