List of works - Denis Deratani Mauá

Closed-Form Solutions in Learning Probabilistic Logic Programs by Exact Score Maximization

scientific article published in 2017

DL-Lite Bayesian Networks: A Tractable Probabilistic Graphical Model

scientific article published in 2015

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

scientific article published in January 2016

Evaluating credal classifiers by utility-discounted predictive accuracy

scientific article published in November 2012

Fast local search methods for solving limited memory influence diagrams

scientific article published in January 2016

Hidden Markov models with set-valued parameters

scientific article published in March 2016

On the complexity of propositional and relational credal networks

scientific article published in April 2017

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

scientific article published in December 2013

Robustifying sum-product networks ⬇️

schorlaly article

Speeding up parameter and rule learning for acyclic probabilistic logic programs

scientific article published in March 2019

The Complexity of Inferences and Explanations in Probabilistic Logic Programming

scientific article published in 2017

The Complexity of Plate Probabilistic Models

scientific article published in 2015

The Descriptive Complexity of Bayesian Network Specifications

scientific article published in 2017

The complexity of Bayesian networks specified by propositional and relational languages ⬇️

scientific article published in September 2018

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

scientific article published in June 2017

Updating credal networks is approximable in polynomial time

scientific article published in November 2012

List of works by Denis Deratani Mauá

Closed-Form Solutions in Learning Probabilistic Logic Programs by Exact Score Maximization

DL-Lite Bayesian Networks: A Tractable Probabilistic Graphical Model

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

Evaluating credal classifiers by utility-discounted predictive accuracy

Fast local search methods for solving limited memory influence diagrams

Hidden Markov models with set-valued parameters

On the complexity of propositional and relational credal networks

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

Robustifying sum-product networks ⬇️

Speeding up parameter and rule learning for acyclic probabilistic logic programs

The Complexity of Inferences and Explanations in Probabilistic Logic Programming

The Complexity of Plate Probabilistic Models

The Descriptive Complexity of Bayesian Network Specifications

The complexity of Bayesian networks specified by propositional and relational languages ⬇️

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

Updating credal networks is approximable in polynomial time