Dealing with cycles in graph-based probabilistic models: the case of Logical Credal Networks (2025)
- Authors:
- USP affiliated authors: COZMAN, FABIO GAGLIARDI - EP ; MAUÁ, DENIS DERATANI - IME
- Unidades: EP; IME
- Subjects: MODELOS PARA PROCESSOS ESTOCÁSTICOS; PROCESSOS DE MARKOV
- Keywords: Credal networks; Cyclic networks; Redes credais
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: MLResearch Press
- Publisher place: Cambridge
- Date published: 2025
- Source:
- Título: Proceedings of Machine Learning Research PMLR
- ISSN: 2640-3498
- Volume/Número/Paginação/Ano: v. 290, p. 93-102, 2025
- Conference titles: International Symposium on Imprecise Probabilities: Theories and Applications - ISIPTA 2025
-
ABNT
COZMAN, Fabio Gagliardi et al. Dealing with cycles in graph-based probabilistic models: the case of Logical Credal Networks. Proceedings of Machine Learning Research PMLR. Cambridge: MLResearch Press. Disponível em: https://proceedings.mlr.press/v290/cozman25a.html. Acesso em: 12 jan. 2026. , 2025 -
APA
Cozman, F. G., Marinescu, R., Lee, J., Gray, A., & Mauá, D. D. (2025). Dealing with cycles in graph-based probabilistic models: the case of Logical Credal Networks. Proceedings of Machine Learning Research PMLR. Cambridge: MLResearch Press. Recuperado de https://proceedings.mlr.press/v290/cozman25a.html -
NLM
Cozman FG, Marinescu R, Lee J, Gray A, Mauá DD. Dealing with cycles in graph-based probabilistic models: the case of Logical Credal Networks [Internet]. Proceedings of Machine Learning Research PMLR. 2025 ; 290 93-102.[citado 2026 jan. 12 ] Available from: https://proceedings.mlr.press/v290/cozman25a.html -
Vancouver
Cozman FG, Marinescu R, Lee J, Gray A, Mauá DD. Dealing with cycles in graph-based probabilistic models: the case of Logical Credal Networks [Internet]. Proceedings of Machine Learning Research PMLR. 2025 ; 290 93-102.[citado 2026 jan. 12 ] Available from: https://proceedings.mlr.press/v290/cozman25a.html - The effect of combination functions on the complexity of relational Bayesian networks
- Complexity results for probabilistic answer set programming
- On the complexity of propositional and relational credal networks
- The descriptive complexity of bayesian network specifications
- Probabilistic logic programming under the L-Stable semantics
- Probabilistic graphical models specified by probabilistic logic programs: semantics and complexit
- The structure and complexity of credal semantics
- Specifying probabilistic relational models with description logics
- The effect of combination functions on the complexity of relational Bayesian networks
- Bayesian networks of bounded treewidth: a performance analysis
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