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...
Asıl Yazarlar: | Tena Cucala, D, Cuenca Grau, B |
---|---|
Materyal Türü: | Conference item |
Dil: | English |
Baskı/Yayın Bilgisi: |
IJCAI Organization
2024
|
Benzer Materyaller
-
On the correspondence between monotonic max-sum GNNs and datalog
Yazar:: Tena Cucala, D, ve diğerleri
Baskı/Yayın Bilgisi: (2023) -
On the correspondence between monotonic max-sum GNNs and Datalog
Yazar:: Tena Cucala, D, ve diğerleri
Baskı/Yayın Bilgisi: (2023) -
Stratified negation in datalog with metric temporal operators
Yazar:: Tena Cucala, D, ve diğerleri
Baskı/Yayın Bilgisi: (2021) -
DatalogMTL with negation under stable models semantics
Yazar:: Wałęga, PA, ve diğerleri
Baskı/Yayın Bilgisi: (2021) -
The stable model semantics of datalog with metric temporal operators
Yazar:: Walega, P, ve diğerleri
Baskı/Yayın Bilgisi: (2023)