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pro vyhledávání: '"Cucala, David J. Tena"'
Graph neural networks (GNNs) are frequently used to predict missing facts in knowledge graphs (KGs). Motivated by the lack of explainability for the outputs of these models, recent work has aimed to explain their predictions using Datalog, a widely u
Externí odkaz:
http://arxiv.org/abs/2408.10261
We introduce negation under the stable model semantics in DatalogMTL - a temporal extension of Datalog with metric temporal operators. As a result, we obtain a rule language which combines the power of answer set programming with the temporal dimensi
Externí odkaz:
http://arxiv.org/abs/2306.07625
Publikováno v:
Theory & Practice of Logic Programming; Jan2024, Vol. 24 Issue 1, p22-56, 35p
