Publications

(2020). Learning Probabilistic Sentential Decision Diagrams by Sampling. Proceedings of the VIII Symposium on Knowledge Discovery, Mining and Learning.
(2020). Finding Feasible Policies for Extreme Risk-Averse Agents in Probabilistic Planning. Proceedings of the 9th Brazilian Conference on Intelligent Systems.
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(2020). Efficient Algorithms for Robustness Analysis of Maximum A Posteriori Inference in Selective Sum-Product Networks. International Journal of Approximate Reasoning.
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(2020). Decision-Aware Model Learning for Actor-Critic Methods: When Theory Does Not Meet Practice. Proceedings of the First I Can’t Believe It’s Not Better Workshop.
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(2020). Complexity results for probabilistic answer set programming. International Journal of Approximate Reasoning.
(2020). A Contact Network-Based Approach for Online Planning of Containment Measures for COVID-19. Anais do XVII Encontro Nacional de Inteligência Artificial e Computacional.
(2019). The finite model theory of Bayesian network specifications: Descriptive complexity and zero/one laws. International Journal of Approximate Reasoning.
(2019). Speeding up parameter and rule learning for acyclic probabilistic logic programs. International Journal of Approximate Reasoning.
(2019). Robust Analysis of MAP Inference in Selective Sum-Product Networks. Proceedings of the 11th International Symposium on Imprecise Probabilities: Theories and Applications.
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(2019). Exploring the Space of Probabilistic Sentential Decision Diagrams. 3rd Tractable Probabilistic Modeling Workshop.
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