Publications

(2021). Learning probabilistic sentential decision diagrams under logic constraints by sampling and averaging. Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence.
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(2021). Fast And Accurate Learning of Probabilistic Circuits by Random Projections. Proceedings of the 4th Workshop on Tractable Probabilistic Modeling.
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(2021). Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget. International Journal of Approximate Reasoning.
(2021). Cautious Classification with Data Missing Not at Random using Generative Random Forests. Proceedings of the Sixteenth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty.
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(2020). Two Reformulation Approaches to Maximum-A-Posteriori Inference in Sum-Product Networks. Proceedings of the Tenth International Conference on Probabilistic Graphical Models.
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(2020). Tractable inference in credal sentential decision diagrams. International Journal of Approximate Reasoning.
(2020). Thirty years of credal networks: Specification, algorithms and complexity. International Journal of Approximate Reasoning.
(2020). The Joy of Probabilistic Answer Set Programming: Semantics, complexity, expressivity, inference. International Journal of Approximate Reasoning.
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(2020). Prediction of Environmental Conditions for Maritime Navigation using a Network of Sensors: A Practical Application of Graph Neural Networks. Proceedings of the VIII Symposium on Knowledge Discovery, Mining and Learning.
(2020). On the Performance of Planning Through Backpropagation. Proceedings of the 9th Brazilian Conference on Intelligent Systems.