Antonio Salmerón

Affiliations:
  • University of Almería, Department of Statistics and Applied Mathematics, Almería, Spain


According to our database1, Antonio Salmerón authored at least 94 papers between 1998 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2021
Probabilistic Models with Deep Neural Networks.
Entropy, 2021

2020
MoTBFs: An R Package for Learning Hybrid Bayesian Networks Using Mixtures of Truncated Basis Functions.
R J., 2020

Comparing two multinomial samples using hierarchical Bayesian models.
Prog. Artif. Intell., 2020

InferPy: Probabilistic modeling with deep neural networks made easy.
Neurocomputing, 2020

Analyzing concept drift: A case study in the financial sector.
Intell. Data Anal., 2020

Analyzing Uncertainty in Complex Socio-Ecological Networks.
Entropy, 2020

Probabilistic Graphical Models with Neural Networks in InferPy.
Proceedings of the International Conference on Probabilistic Graphical Models, 2020

2019
A survey on Bayesian network structure learning from data.
Prog. Artif. Intell., 2019

AMIDST: A Java toolbox for scalable probabilistic machine learning.
Knowl. Based Syst., 2019

InferPy: Probabilistic modeling with Tensorflow made easy.
Knowl. Based Syst., 2019

Prediction of a complex system with few data: Evaluation of the effect of model structure and amount of data with dynamic bayesian network models.
Environ. Model. Softw., 2019

2018
A Review of Inference Algorithms for Hybrid Bayesian Networks.
J. Artif. Intell. Res., 2018

Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks.
Int. J. Approx. Reason., 2018

2017
MAP inference in dynamic hybrid Bayesian networks.
Prog. Artif. Intell., 2017

A parallel algorithm for Bayesian network structure learning from large data sets.
Knowl. Based Syst., 2017

Scaling up Bayesian variational inference using distributed computing clusters.
Int. J. Approx. Reason., 2017

Bayesian Models of Data Streams with Hierarchical Power Priors.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Modeling zero-inflated explanatory variables in hybrid Bayesian network classifiers for species occurrence prediction.
Environ. Model. Softw., 2016

Parameter learning in hybrid Bayesian networks using prior knowledge.
Data Min. Knowl. Discov., 2016

Scalable MAP inference in Bayesian networks based on a Map-Reduce approach.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

d-VMP: Distributed Variational Message Passing.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

Financial Data Analysis with PGMs Using AMIDST.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015
Continuous Bayesian networks for the estimation of species richness.
Prog. Artif. Intell., 2015

Practical Aspects of Solving Hybrid Bayesian Networks Containing Deterministic Conditionals.
Int. J. Intell. Syst., 2015

Recent Advances in Probabilistic Graphical Models.
Int. J. Intell. Syst., 2015

Dynamic Bayesian modeling for risk prediction in credit operations.
Proceedings of the Thirteenth Scandinavian Conference on Artificial Intelligence, 2015

Modeling Concept Drift: A Probabilistic Graphical Model Based Approach.
Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

MPE Inference in Conditional Linear Gaussian Networks.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

Learning Conditional Distributions Using Mixtures of Truncated Basis Functions.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

Parallel Importance Sampling in Conditional Linear Gaussian Networks.
Proceedings of the Advances in Artificial Intelligence, 2015

Estimation of Species Richness Using Bayesian Networks.
Proceedings of the Advances in Artificial Intelligence, 2015

Parallelisation of the PC Algorithm.
Proceedings of the Advances in Artificial Intelligence, 2015

2014
Data clustering using hidden variables in hybrid Bayesian networks.
Prog. Artif. Intell., 2014

A tool based on Bayesian networks for supporting geneticists in plant improvement by controlled pollination.
Int. J. Approx. Reason., 2014

Learning mixtures of truncated basis functions from data.
Int. J. Approx. Reason., 2014

A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Supervised Classification Using Hybrid Probabilistic Decision Graphs.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Requirement Engineering for a Small Project with Pre-Specified Scope.
Proceedings of the 27th Norsk Informatikkonferanse, 2014

2013
Inference in Bayesian Networks with Recursive Probability Trees: Data Structure Definition and Operations.
Int. J. Intell. Syst., 2013

Inventory management with log-normal demand per unit time.
Comput. Oper. Res., 2013

New strategies for finding multiplicative decompositions of probability trees.
Appl. Math. Comput., 2013

Incorporating Prior Knowledge when Learning Mixtures of Truncated Basis Functions from Data.
Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence, 2013

Learning Recursive Probability Trees from Data.
Proceedings of the Advances in Artificial Intelligence, 2013

On Using the PC Algorithm for Learning Continuous Bayesian Networks: An Experimental Analysis.
Proceedings of the Advances in Artificial Intelligence, 2013

2012
Fast Factorisation of Probabilistic Potentials and its Application to Approximate Inference in Bayesian Networks.
Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2012

Modelling and inference with Conditional Gaussian Probabilistic Decision Graphs.
Int. J. Approx. Reason., 2012

Mixtures of truncated basis functions.
Int. J. Approx. Reason., 2012

Learning recursive probability trees from probabilistic potentials.
Int. J. Approx. Reason., 2012

Answering queries in hybrid Bayesian networks using importance sampling.
Decis. Support Syst., 2012

Moments and associated measures of copulas with fractal support.
Appl. Math. Comput., 2012

2011
A system for relevance analysis of performance indicators in higher education using Bayesian networks.
Knowl. Inf. Syst., 2011

Bayesian networks in environmental modelling.
Environ. Model. Softw., 2011

Some practical issues in inference in hybrid Bayesian networks with deterministic conditionals.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

Mixture of truncated exponentials in supervised classification: Case study for the naive bayes and averaged one-dependence estimators classifiers.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

2010
Learning Bayesian Networks for Regression from Incomplete Databases.
Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2010

Structural-EM for learning PDG models from incomplete data.
Int. J. Approx. Reason., 2010

Parameter estimation and model selection for mixtures of truncated exponentials.
Int. J. Approx. Reason., 2010

Probability Tree Factorisation with Median Free Term.
Proceedings of the Combining Soft Computing and Statistical Methods in Data Analysis, 2010

Fast Factorization of Probability Trees and Its Application to Recursive Trees Learning.
Proceedings of the Combining Soft Computing and Statistical Methods in Data Analysis, 2010

Conditional Gaussian Probabilistic Decision Graphs.
Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

2009
Inference in hybrid Bayesian networks.
Reliab. Eng. Syst. Saf., 2009

Supervised classification using probabilistic decision graphs.
Comput. Stat. Data Anal., 2009

Maximum Likelihood Learning of Conditional MTE Distributions.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2009

Predicting Stock and Portfolio Returns Using Mixtures of Truncated Exponentials.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2009

2008
BayesChess: A computer chess program based on Bayesian networks.
Pattern Recognit. Lett., 2008

Extension of Bayesian Network Classifiers to Regression Problems.
Proceedings of the Advances in Artificial Intelligence, 2008

2007
Selective Naive Bayes for Regression Based on Mixtures of Truncated Exponentials.
Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2007

Approximate probability propagation with mixtures of truncated exponentials.
Int. J. Approx. Reason., 2007

Tree Augmented Naive Bayes for Regression Using Mixtures of Truncated Exponentials: Application to Higher Education Management.
Proceedings of the Advances in Intelligent Data Analysis VII, 2007

2006
Learning hybrid Bayesian networks using mixtures of truncated exponentials.
Int. J. Approx. Reason., 2006

Special issue on PGM'04: Second European workshop on probabilistic graphical models 2004.
Int. J. Approx. Reason., 2006

Dynamic importance sampling in Bayesian networks using factorisation of probability trees.
Proceedings of the Third European Workshop on Probabilistic Graphical Models, 2006

Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials.
Proceedings of the Third European Workshop on Probabilistic Graphical Models, 2006

2005
Dynamic importance sampling in Bayesian networks based on probability trees.
Int. J. Approx. Reason., 2005

Modeling Conditional Distributions of Continuous Variables in Bayesian Networks.
Proceedings of the Advances in Intelligent Data Analysis VI, 2005

Penniless Propagation with Mixtures of Truncated Exponentials.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2005

Approximate Factorisation of Probability Trees.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2005

2003
Probabilistic graphical models.
Int. J. Intell. Syst., 2003

Novel strategies to approximate probability trees in penniless propagation.
Int. J. Intell. Syst., 2003

Dynamic Importance Sampling Computation in Bayesian Networks.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2003

Approximating Conditional MTE Distributions by Means of Mixed Trees.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2003

Representing Canonical Models as Probability Trees.
Proceedings of the Current Topics in Artificial Intelligence, 2003

2002
Lazy evaluation in penniless propagation over join trees.
Networks, 2002

Different strategies to approximate probability trees in penniless propagation.
Inteligencia Artif., 2002

Estimating Mixtures of Truncated Exponentials from Data.
Proceedings of the First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002, 2002

Factorisation of Probability Trees and its Application to Inference in Bayesian Networks.
Proceedings of the First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002, 2002

2001
Importance Sampling in Bayesian Networks Using Antithetic Variables.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2001

Mixtures of Truncated Exponentials in Hybrid Bayesian Networks.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2001

2000
Operational Approach to General Fuzzy Measures.
Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2000

Penniless propagation in join trees.
Int. J. Intell. Syst., 2000

1999
Towards an Operational Interpretation of Fuzzy Measures.
Proceedings of the ISIPTA '99, Proceedings of the First International Symposium on Imprecise Probabilities and Their Applications, held at the Conference Center "Het Pand" of the Universiteit Gent, Ghent, Belgium, 29 June, 1999

A Monte Carlo Algorithm for Combining Dempster-Shafer Belief Based on Approximate Pre-computation.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning and Uncertainty, 1999

1998
A Monte Carlo algorithm for probabilistic propagation in belief networks based on importance sampling and stratified simulation techniques.
Int. J. Approx. Reason., 1998


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