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,...
المؤلفون الرئيسيون: | Tena Cucala, DJ, Cuenca Grau, B, Motik, B |
---|---|
التنسيق: | Conference item |
اللغة: | English |
منشور في: |
IJCAI Organization
2022
|
مواد مشابهة
-
Faithful rule extraction for differentiable rule learning models
حسب: Wang, X, وآخرون
منشور في: (2024) -
Relational graph convolutional networks do not learn sound rules
حسب: Morris, M, وآخرون
منشور في: (2024) -
Explainable GNN-based models over knowledge graphs
حسب: Tena Cucala, DJ, وآخرون
منشور في: (2022) -
On the correspondence between monotonic max-sum GNNs and datalog
حسب: Tena Cucala, D, وآخرون
منشور في: (2023) -
On the correspondence between monotonic max-sum GNNs and Datalog
حسب: Tena Cucala, D, وآخرون
منشور في: (2023)