Bridging max graph neural networks and datalog with negation
We consider a general class of data transformations based on Graph Neural Networks (GNNs), which can be used for a wide variety of tasks. An important question in this setting is characterising the expressive power of these transformations in terms of a suitable logic-based language. From a practica...
主要な著者: | , |
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フォーマット: | Conference item |
言語: | English |
出版事項: |
IJCAI Organization
2024
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