D. Mauá

发表

Decision-Aware Model Learning for Actor-Critic Methods: When Theory Does Not Meet Practice

Â. G. Lovatto, T. P. Bueno, D. Mauá, 2020, ICBINB@NeurIPS.

Algorithms and complexity results for discrete probabilistic reasoning tasks

D. Mauá, 2013 .

Managing Trust in Virtual Communities with Markov Logic

Fabio Gagliardi Cozman, D. Mauá, 2022 .

Learning Probabilistic Sentential Decision Diagrams by Sampling

Alessandro Antonucci, D. Mauá, R. L. Geh, 2020 .

Exploring the Space of Probabilistic Sentential Decision Diagrams

Alessandro Antonucci, D. Mauá, Alessandro Facchini, 2019 .

Improving Acyclic Selection Order-Based Bayesian Network Structure Learning

Walter Perez Urcia, D. Mauá, 2016 .

Hidden Markov Models With Imprecisely Specified Parameters

Alessandro Antonucci, D. Mauá, 2014 .

Bayesian Networks of Bounded Treewidth: A Performance Analysis

Fabio Gagliardi Cozman, D. Mauá, Fabio H. S. Machado, 2015 .

Two Reformulation Approaches to Maximum-A-Posteriori Inference in Sum-Product Networks

D. Mauá, H. R. Ribeiro, 2020, PGM.

Initialization Heuristics for Greedy Bayesian Network Structure Learning

Walter Perez Urcia, D. Mauá, 2015 .

Distinct Outcomes in COVID-19 Patients with Positive or Negative RT-PCR Test

D. Mauá, Izabel Marcilio, J. Ferreira, 2022, Viruses.

Differentiable Planning for Optimal Liquidation

D. Mauá, L. N. Barros, Alan A. Pennacchio, 2022, Anais do I Brazilian Workshop on Artificial Intelligence in Finance (BWAIF 2022).

Robustifying sum-product networks

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2018, Int. J. Approx. Reason..

Hidden Markov models with set-valued parameters

Denis Deratani Mauá, Alessandro Antonucci, Cassio Polpo de Campos, 2016, Neurocomputing.

The BLue Amazon Brain (BLAB): A Modular Architecture of Services about the Brazilian Maritime Territory

Vinícius Bitencourt Matos, F. Cozman, D. Mauá, 2022, ArXiv.

Timing to Intubation COVID-19 Patients: Can We Put It Off until Tomorrow?

C. Carvalho, D. Mauá, Izabel Marcilio, 2021, Healthcare.

Integrating question answering and text-to-SQL in Portuguese

F. Cozman, D. Mauá, M. A. Jos'e, 2022, PROPOR.

The Finite Model Theory of Bayesian Networks: Descriptive Complexity

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2018, IJCAI.

Speeding-up ProbLog's Parameter Learning pdf

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2017, ArXiv.

The Descriptive Complexity of Bayesian Network Specifications

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2017, ECSQARU.

On the complexity of propositional and relational credal networks

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2017, Int. J. Approx. Reason..

DL-Lite Bayesian Networks: A Tractable Probabilistic Graphical Model

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2015, SUM.

Bayesian Networks Specified Using Propositional and Relational Constructs: Combined, Data, and Domain Complexity

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2015, AAAI.

Markov Decision Processes Specified by Probabilistic Logic Programming: Representation and Solution

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2016, 2016 5th Brazilian Conference on Intelligent Systems (BRACIS).

An Ensemble of Bayesian Networks for Multilabel Classification

Denis Deratani Mauá, Giorgio Corani, Alessandro Antonucci, 2013, IJCAI.

The joy of Probabilistic Answer Set Programming: Semantics, complexity, expressivity, inference

Denis Deratani Mauá, Fábio Gagliardi Cozman, F. Cozman, 2020, Int. J. Approx. Reason..

On the Semantics and Complexity of Probabilistic Logic Programs

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2017, J. Artif. Intell. Res..

Probabilistic Inference in Credal Networks: New Complexity Results

Denis Deratani Mauá, Alessio Benavoli, Alessandro Antonucci, 2014, J. Artif. Intell. Res..

Deep Reactive Policies for Planning in Stochastic Nonlinear Domains

Scott Sanner, Denis Deratani Mauá, Leliane Nunes de Barros, 2019, AAAI.

Thirty years of credal networks: Specification, algorithms and complexity

Denis Deratani Mauá, Fábio Gagliardi Cozman, D. Mauá, 2020, Int. J. Approx. Reason..

The Complexity of MAP Inference in Bayesian Networks Specified Through Logical Languages

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2015, IJCAI.

Advances in Automatically Solving the ENEM

Denis Deratani Mauá, Igor Cataneo Silveira, D. Mauá, 2018, BRACIS.

Speeding up parameter and rule learning for acyclic probabilistic logic programs

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2019, Int. J. Approx. Reason..

The Complexity of Bayesian Networks Specified by Propositional and Relational Languages pdf

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2016, Artif. Intell..

Credal Sum-Product Networks

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2017, ISIPTA.

The effect of combination functions on the complexity of relational Bayesian networks

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2016, Int. J. Approx. Reason..

Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2016, Probabilistic Graphical Models.

Trading off Speed and Accuracy in Multilabel Classification

Denis Deratani Mauá, Giorgio Corani, Alessandro Antonucci, 2014, Probabilistic Graphical Models.

Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams

Denis Deratani Mauá, D. Mauá, 2014, Int. J. Approx. Reason..

On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables

Denis Deratani Mauá, Marco Zaffalon, Cassio Polpo de Campos, 2013, Artif. Intell..

Fast local search methods for solving limited memory influence diagrams

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2016, Int. J. Approx. Reason..

Tractable Mode-Finding in Sum-Product Networks with Gaussian Leaves

D. Mauá, Tiago Madeira, 2022, Anais do XIX Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2022).

dPASP: A Comprehensive Differentiable Probabilistic Answer Set Programming Environment For Neurosymbolic Learning and Reasoning

Fabio Gagliardi Cozman, Renato Lui Geh, D. Mauá, 2023, 2308.02944.

Tractable Inference in Credal Sentential Decision Diagrams

Alessandro Facchini, Alessandro Antonucci, Julissa Villanueva Llerena, 2020, Int. J. Approx. Reason..

Evaluating credal classifiers by utility-discounted predictive accuracy

Denis Deratani Mauá, Marco Zaffalon, Giorgio Corani, 2012, Int. J. Approx. Reason..

Tractable Classification with Non-Ignorable Missing Data Using Generative Random Forests

D. Mauá, Julissa Villanueva, 2022, Anais do X Symposium on Knowledge Discovery, Mining and Learning (KDMiLe 2022).

Better Initialization Heuristics for Order-based Bayesian Network Structure Learning

Denis Deratani Mauá, Walter Perez Urcia, D. Mauá, 2017, J. Inf. Data Manag..

Solving Decision Problems with Limited Information

Denis Deratani Mauá, Cassio Polpo de Campos, Cassio Polpo de Campos, 2011, NIPS.

Solving Limited Memory Influence Diagrams

Denis Deratani Mauá, Marco Zaffalon, Cassio Polpo de Campos, 2011, J. Artif. Intell. Res..

Medical Data Mining Using Evolutionary Computation

Kwong-Sak Leung, Wai Lam, Simone Paolo Ponzetto, 2022 .

Speeding Up k-Neighborhood Local Search in Limited Memory Influence Diagrams

Denis Deratani Mauá, Fabio Gagliardi Cozman, Fábio Gagliardi Cozman, 2014, Probabilistic Graphical Models.

Differentiable Planning with Indefinite Horizon

Daniel B. Dias, D. Mauá, Leliane N. de Barros, 2022, Anais do X Symposium on Knowledge Discovery, Mining and Learning (KDMiLe 2022).

When a Robot Reaches Out for Human Help

Denis Deratani Mauá, Thiago D. Simão, Leliane Nunes de Barros, 2018, IBERAMIA.

Advances in Learning Bayesian Networks of Bounded Treewidth pdf

Qiang Ji, Denis Deratani Mauá, Cassio Polpo de Campos, 2014, NIPS.

On the Complexity of Strong and Epistemic Credal Networks pdf

Denis Deratani Mauá, Alessio Benavoli, Alessandro Antonucci, 2013, UAI.

On Using Sum-Product Networks for Multi-label Classification

Denis Deratani Mauá, Julissa Villanueva Llerena, Julissa Giuliana Villanueva Llerena, 2017, 2017 Brazilian Conference on Intelligent Systems (BRACIS).

Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks pdf

Denis Deratani Mauá, Cassio Polpo de Campos, Diarmaid Conaty, 2017, UAI.

Updating credal networks is approximable in polynomial time

Denis Deratani Mauá, Marco Zaffalon, Cassio Polpo de Campos, 2012, Int. J. Approx. Reason..

International Journal of Approximate Reasoning

Fabio Gagliardi Cozman, Glauber De Bona, D. Mauá, 2022 .

The Well-Founded Semantics of Cyclic Probabilistic Logic Programs : Meaning and Complexity

Denis Deratani Mauá, Fabio Gagliardi Cozman, D. Mauá, 2016 .