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Denis Deratani Mauá
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Distinct Outcomes in COVID-19 Patients with Positive or Negative RT-PCR Test
Integrating Question Answering and Text-to-SQL in Portuguese
Timing to Intubation COVID-19 Patients: Can We Put It Off until Tomorrow?
Cautious Classification with Data Missing Not at Random using Generative Random Forests
Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget
Fast And Accurate Learning of Probabilistic Circuits by Random Projections
Learning Probabilistic Sentential Decision Diagrams under Logic Constraints by Sampling and Averaging
Complexity results for probabilistic answer set programming
Efficient Algorithms for Robustness Analysis of Maximum A Posteriori Inference in Selective Sum-Product Networks
The Joy of Probabilistic Answer Set Programming: Semantics, complexity, expressivity, inference
Thirty years of credal networks: Specification, algorithms and complexity
Tractable inference in credal sentential decision diagrams
Two Reformulation Approaches to Maximum-A-Posteriori Inference in Sum-Product Networks
Deep Reactive Policies for Planning in Stochastic Nonlinear Domains
End-To-End Imitation Learning of Lane Following Policies Using Sum-Product Networks
Exploring the Space of Probabilistic Sentential Decision Diagrams
Robust Analysis of MAP Inference in Selective Sum-Product Networks
Speeding up parameter and rule learning for acyclic probabilistic logic programs
The finite model theory of Bayesian network specifications: Descriptive complexity and zero/one laws
The Finite Model Theory of Bayesian Networks: Descriptive Complexity
Advances in Automatically Solving the ENEM
Robustifying sum-product networks
The complexity of Bayesian networks specified by propositional and relational languages
When a Robot Reaches Out for Human Help
Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks
Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks
Closed-Form Solutions in Learning Probabilistic Logic Programs by Exact Score Maximization
Credal Sum-Product Networks
Modeling Markov Decision Processes with Imprecise Probabilities Using Probabilistic Logic Programming
On the complexity of propositional and relational credal networks
On the Semantics and Complexity of Probabilistic Logic Programs
On Using Sum-Product Networks For Multi-Label Classification
Parameter Learning in ProbLog with Probabilistic Rules
Speeding-up ProbLog's Parameter Learning
The Complexity of Inferences and Explanations in Probabilistic Logic Programming
The Descriptive Complexity of Bayesian Network Specifications
The effect of combination functions on the complexity of relational Bayesian networks
University Entrance Exam as a Guiding Test for Artificial Intelligence
The Complexity of Bayesian Networks Specified by Propositional and Relational Languages
Better Initialization Heuristics for Order-based Bayesian Network Structure Learning
Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams
Fast local search methods for solving limited memory influence diagrams
Hidden Markov models with set-valued parameters
Improving Acyclic Selection Order-Based Bayesian Network Structure Learning
Markov Decision Processes Specified by Probabilistic Logic Programming: Representation and Solution
Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity
The Effect of Combination Functions on the Complexity of Relational Bayesian Networks
The structure and complexity of credal semantics
The Well-Founded Semantics of Cyclic Probabilistic Logic Programs
A Tractable Class of Model Counting Problems
Bayesian Networks of Bounded Treewith: A Performance Analysis
Bayesian Networks Specified Using Propositional and Relational Constructs: Combined, Data, and Domain Complexity
DL-Lite Bayesian Networks: A Tractable Probabilistic Graphical Model
Initialization Heuristics for Greedy Bayesian Network Structure Learning
On the Complexity of Propositional and Relational Credal Networks
Specifying Probabilistic Relational Models with Description Logics
The Complexity of MAP Inference in Bayesian Networks Specified Through Logical Languages
The Complexity of Plate Probabilistic Models
Advances in Learning Bayesian Networks of Bounded Treewidth
Advances in Learning Bayesian Networks of Bounded Treewidth
Algorithms for Hidden Markov Models With Imprecisely Specified Parameters
Equivalences between Maximum a Posteriori Inference in Bayesian Networks and Maximum Expected Utility Computation in Influence Diagrams
Probabilistic Inference in Credal Networks: New Complexity Results
Speeding Up k-Neighborhood Local Search in Limited Memory Influence Diagrams
Trading off Speed and Accuracy in Multilabel Classification
Algorithms and Complexity Results for Discrete Probabilistic Reasoning Tasks
An Ensemble of Bayesian Networks for Multilabel Classification
On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables
On the Complexity of Strong and Epistemic Credal Networks
Anytime Marginal MAP Inference
Evaluating credal classifiers by utility-discounted predictive accuracy
Solving Limited Memory Influence Diagrams
The Complexity of Approximately Solving Influence Diagrams
Updating Credal Networks is Approximable in Polynomial Time
Solving Limited Memory Influence Diagrams
A Fully Polynomial Time Approximation Scheme for Updating Credal Networks of Bounded Treewidth and Number of Variable States
Solving Decision Problems with Limited Information
Utility-Based Accuracy Measures to Empirically Evaluate Credal Classifiers
Representing and Classifying User Reviews
Topic models on the automatic classification of user reviews
Managing Trust in Virtual Communities with Markov Logic
Using Social Data to Predict Trust on Web Communities : A Case Study with the Epinions.com Website
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