The finite model theory of bayesian networks: descriptive complexity (2018)
- Authors:
- USP affiliated authors: MAUÁ, DENIS DERATANI - IME ; COZMAN, FABIO GAGLIARDI - EP
- Unidades: IME; EP
- DOI: 10.24963/ijcai.2018/727
- Subjects: COMPUTABILIDADE E COMPLEXIDADE; INTELIGÊNCIA ARTIFICIAL; INFERÊNCIA BAYESIANA
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- Conference titles: International Joint Conference on Artificial Intelligence - IJCAI
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
COZMAN, Fabio Gagliardi e MAUÁ, Denis Deratani. The finite model theory of bayesian networks: descriptive complexity. 2018, Anais.. Vienna: IJCAI, 2018. Disponível em: https://doi.org/10.24963/ijcai.2018/727. Acesso em: 09 fev. 2026. -
APA
Cozman, F. G., & Mauá, D. D. (2018). The finite model theory of bayesian networks: descriptive complexity. In Proceedings. Vienna: IJCAI. doi:10.24963/ijcai.2018/727 -
NLM
Cozman FG, Mauá DD. The finite model theory of bayesian networks: descriptive complexity [Internet]. Proceedings. 2018 ;[citado 2026 fev. 09 ] Available from: https://doi.org/10.24963/ijcai.2018/727 -
Vancouver
Cozman FG, Mauá DD. The finite model theory of bayesian networks: descriptive complexity [Internet]. Proceedings. 2018 ;[citado 2026 fev. 09 ] Available from: https://doi.org/10.24963/ijcai.2018/727 - Dealing with cycles in graph-based probabilistic models: the case of Logical Credal Networks
- The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference
- Thirty years of credal networks: specification, algorithms and complexity
- Probabilistic logic programming under the L-Stable semantics
- Specifying credal sets with probabilistic answer set programming
- The complexity of inferences and explanations in probabilistic logic programming
- The descriptive complexity of bayesian network specifications
- Robustifying sum-product networks
- The complexity of Bayesian networks specified by propositional and relational languages
- Complexity results for probabilistic answer set programming
Informações sobre o DOI: 10.24963/ijcai.2018/727 (Fonte: oaDOI API)
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