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Trabalho de evento
The finite model theory of bayesian networks: descriptive complexity (2018)
Cozman, Fabio Gagliardi ; Mauá, Denis Deratani
Fonte: Proceedings. Nome do evento: International Joint Conference on Artificial Intelligence - IJCAI. Unidades: IME, EP
Assuntos: COMPUTABILIDADE E COMPLEXIDADE, INTELIGÊNCIA ARTIFICIAL, INFERÊNCIA BAYESIANA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 27 nov. 2025.
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 2025 nov. 27 ] 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 2025 nov. 27 ] Available from: https://doi.org/10.24963/ijcai.2018/727
Trabalho de evento
The complexity of MAP inference in Bayesian networks specified through logical languages (2015)
Mauá, Denis Deratani ; Campos, Cassio Polpo de; Cozman, Fabio Gagliardi
Fonte: Proceedings. Nome do evento: International Joint Conference on Artificial Intelligence - IJCAI. Unidades: IME, EP
Assuntos: COMPUTABILIDADE E COMPLEXIDADE, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MAUÁ, Denis Deratani e CAMPOS, Cassio Polpo de e COZMAN, Fabio Gagliardi. The complexity of MAP inference in Bayesian networks specified through logical languages. 2015, Anais.. Palo Alto: AAAI Press / International Joint Conferences on Artificial Intelligence, 2015. Disponível em: http://ijcai.org/papers15/Papers/IJCAI15-130.pdf. Acesso em: 27 nov. 2025.
APA
Mauá, D. D., Campos, C. P. de, & Cozman, F. G. (2015). The complexity of MAP inference in Bayesian networks specified through logical languages. In Proceedings. Palo Alto: AAAI Press / International Joint Conferences on Artificial Intelligence. Recuperado de http://ijcai.org/papers15/Papers/IJCAI15-130.pdf
NLM
Mauá DD, Campos CP de, Cozman FG. The complexity of MAP inference in Bayesian networks specified through logical languages [Internet]. Proceedings. 2015 ;[citado 2025 nov. 27 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-130.pdf
Vancouver
Mauá DD, Campos CP de, Cozman FG. The complexity of MAP inference in Bayesian networks specified through logical languages [Internet]. Proceedings. 2015 ;[citado 2025 nov. 27 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-130.pdf
Trabalho de evento
Probabilistic satisfiability: logic-based algorithms and phase transition (2011)
Finger, Marcelo ; De Bona, Glauber
Fonte: Proceedings. Nome do evento: International Joint Conference on Artificial Intelligence - IJCAI. Unidade: IME
Assuntos: INTELIGÊNCIA ARTIFICIAL, RACIOCÍNIO PROBABILÍSTICO, COMPUTABILIDADE E COMPLEXIDADE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FINGER, Marcelo e DE BONA, Glauber. Probabilistic satisfiability: logic-based algorithms and phase transition. 2011, Anais.. Palo Alto: AAAI Press, 2011. Disponível em: https://doi.org/10.5555/2283396.2283483. Acesso em: 27 nov. 2025.
APA
Finger, M., & De Bona, G. (2011). Probabilistic satisfiability: logic-based algorithms and phase transition. In Proceedings. Palo Alto: AAAI Press. doi:10.5555/2283396.2283483
NLM
Finger M, De Bona G. Probabilistic satisfiability: logic-based algorithms and phase transition [Internet]. Proceedings. 2011 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.5555/2283396.2283483
Vancouver
Finger M, De Bona G. Probabilistic satisfiability: logic-based algorithms and phase transition [Internet]. Proceedings. 2011 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.5555/2283396.2283483

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