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cs.AI2025
Aggregate-Combine-Readout GNNs Are More Expressive Than Logic C2
Stan P Hauke, Przemysław Andrzej Wałęga
In recent years, there has been growing interest in understanding the expressive power of graph neural networks (GNNs) by relating them to logical languages. This research has been…
cs.AI2025
The Correspondence Between Bounded Graph Neural Networks and Fragments of First-Order Logic
Bernardo Cuenca Grau, Eva Feng, Przemysław Andrzej Wałęga
Graph Neural Networks (GNNs) address two key challenges in applying deep learning to graph-structured data: they handle varying size input graphs and ensure invariance under graph…