Faithful approaches to rule learning
Rule learning involves developing machine learning models that can be applied to a set of logical facts to predict additional facts, as well as providing methods for extracting from the learned model a set of logical rules that explain symbolically the model’s predictions. Existing such approaches,...
Hoofdauteurs: | Tena Cucala, DJ, Cuenca Grau, B, Motik, B |
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Formaat: | Conference item |
Taal: | English |
Gepubliceerd in: |
IJCAI Organization
2022
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Gelijkaardige items
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Faithful rule extraction for differentiable rule learning models
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Relational graph convolutional networks do not learn sound rules
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Explainable GNN-based models over knowledge graphs
door: Tena Cucala, DJ, et al.
Gepubliceerd in: (2022) -
On the correspondence between monotonic max-sum GNNs and datalog
door: Tena Cucala, D, et al.
Gepubliceerd in: (2023) -
On the correspondence between monotonic max-sum GNNs and Datalog
door: Tena Cucala, D, et al.
Gepubliceerd in: (2023)