On the correspondence between monotonic max-sum GNNs and datalog
Although there has been significant interest in applying machine learning techniques to structured data, the expressivity (i.e., a description of what can be learned) of such techniques is still poorly understood. In this paper, we study data transformations based on graph neural networks (GNNs). Fi...
Κύριοι συγγραφείς: | Tena Cucala, D, Cuenca Grau, B, Motik, B, Kostylev, EV |
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Μορφή: | Conference item |
Γλώσσα: | English |
Έκδοση: |
Association for Computing Machinery
2023
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Παρόμοια τεκμήρια
Παρόμοια τεκμήρια
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On the correspondence between monotonic max-sum GNNs and Datalog
ανά: Tena Cucala, D, κ.ά.
Έκδοση: (2023) -
Bridging max graph neural networks and datalog with negation
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DatalogMTL with negation under stable models semantics
ανά: Wałęga, PA, κ.ά.
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Stratified negation in datalog with metric temporal operators
ανά: Tena Cucala, D, κ.ά.
Έκδοση: (2021) -
The stable model semantics of datalog with metric temporal operators
ανά: Walega, P, κ.ά.
Έκδοση: (2023)