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Logic Tensor Networks for Semantic Image Interpretation

, , и . CoRR, (2017)

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Márcio Rosa D'Avila

Marco André d'Ávila Carvalho

Edelweis Helena Ache Garcez

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S Ulrich

 

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Applying the connectionist inductive learning and logic programming system to power system diagnosis., , и . ICNN, стр. 121-126. IEEE, (1997)Neuro-symbolic Representation of Logic Programs Defining Infinite Sets., , и . ICANN (1), том 6352 из Lecture Notes in Computer Science, стр. 301-304. Springer, (2010)Multi-instance learning using recurrent neural networks., и . IJCNN, стр. 1-6. IEEE, (2012)Neural-symbolic cognitive agents: architecture, theory and application., , , и . AAMAS, стр. 1621-1622. IFAAMAS/ACM, (2014)Learning to adapt requirements specifications of evolving systems., , , и . ICSE, стр. 856-859. ACM, (2011)Improving VG-RAM Neural Networks Performance Using Knowledge Correlation., , , , , и . ICONIP (1), том 4232 из Lecture Notes in Computer Science, стр. 427-436. Springer, (2006)Measurable Counterfactual Local Explanations for Any Classifier., и . ECAI, том 325 из Frontiers in Artificial Intelligence and Applications, стр. 2529-2535. IOS Press, (2020)Reasoning about Time and Knowledge in Neural Symbolic Learning Systems., и . NIPS, стр. 921-928. MIT Press, (2003)Continual Reasoning: Non-monotonic Reasoning in Neurosymbolic AI using Continual Learning., и . NeSy, том 3432 из CEUR Workshop Proceedings, стр. 210-222. CEUR-WS.org, (2023)Inductive Learning in Shared Neural Multi-Spaces., , и . NeSy, том 2003 из CEUR Workshop Proceedings, CEUR-WS.org, (2017)