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...
| Main Authors: | , |
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| Format: | Conference item |
| Language: | English |
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International Conference on Knowledge Representation and Reasoning
2024
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