Antonio Salmerón

发表

Factorisation of Probability Trees and its Applications

Irene Martínez, Serafín Moral, Carmelo Rodríguez, 2002 .

Lazy evaluation in penniless propagation over join trees

Serafín Moral, Antonio Salmerón, Andrés Cano, 2002, Networks.

A parallel algorithm for Bayesian network structure learning from large data sets

Anders L. Madsen, Antonio Salmerón, Thomas D. Nielsen, 2017, Knowl. Based Syst..

Extension of Bayesian Network Classifiers to Regression Problems

Antonio Salmerón, Antonio Fernández, 2008, IBERAMIA.

Scaling up Bayesian variational inference using distributed computing clusters

Andrés R. Masegosa, Anders L. Madsen, Antonio Salmerón, 2017, Int. J. Approx. Reason..

Towards an Operational Interpretation of Fuzzy Measures

Antonio Salmerón, Fernando Reche, 1999, ISIPTA.

HUGIN architecture for propagating belief functions

Antonio Salmerón, Finn V. Jensen, F. V. Jensen, 2012 .

Different strategies to approximate probability trees in penniless propagation

Serafín Moral, Antonio Salmerón, Andrés Cano, 2002, Inteligencia Artif..

Modeling zero-inflated explanatory variables in hybrid Bayesian network classifiers for species occurrence prediction

Antonio Salmerón, Pedro A. Aguilera, A. D. Maldonado, 2016, Environ. Model. Softw..

Variational Inference over Nonstationary Data Streams for Exponential Family Models

Andrés R. Masegosa, Antonio Salmerón, Darío Ramos-López, 2020, Mathematics.

Mixtures of Gaussians as a Proxy in Hybrid Bayesian Networks

Antonio Salmerón, Fernando Reche, 2018 .

Algorithms for Approximate Probability Propagation in Bayesian Networks

Serafín Moral, Antonio Salmerón, Andrés Cano, 2004 .

MPE Inference in Conditional Linear Gaussian Networks

Rafael Rumí, Anders L. Madsen, Antonio Salmerón, 2015, ECSQARU.

Special issue on PGM'04: Second European workshop on probabilistic graphical models 2004

José A. Gámez, Peter J. F. Lucas, Antonio Salmerón, 2006, Int. J. Approx. Reason..

Dynamic importance sampling in Bayesian networks using factorisation of probability trees

Irene Martínez, Carmelo Rodríguez, Antonio Salmerón, 2006, Probabilistic Graphical Models.

Novel strategies to approximate probability trees in penniless propagation

Serafín Moral, Antonio Salmerón, Andrés Cano, 2003, Int. J. Intell. Syst..

A Monte Carlo algorithm for probabilistic propagation in belief networks based on importance sampling and stratified simulation techniques

Serafín Moral, Antonio Salmerón, Luis D. Hernández, 1998, Int. J. Approx. Reason..

Parameter learning in hybrid Bayesian networks using prior knowledge

Rafael Rumí, Antonio Salmerón, Antonio Fernández, 2015, Data Mining and Knowledge Discovery.

A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs

Anders L. Madsen, Antonio Salmerón, Thomas D. Nielsen, 2014, Probabilistic Graphical Models.

InferPy: Probabilistic modeling with Tensorflow made easy

Andrés R. Masegosa, Antonio Salmerón, Rafael Cabañas, 2019, Knowl. Based Syst..

Moments and associated measures of copulas with fractal support

Juan Fernández-Sánchez, Antonio Salmerón, Enrique de Amo, 2012, Appl. Math. Comput..

A Monte Carlo Algorithm for Combining Dempster-Shafer Belief Based on Approximate Pre-computation

Serafín Moral, Antonio Salmerón, 1999, ESCQARU.

Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks

Andrés R. Masegosa, Rafael Rumí, Anders L. Madsen, 2018, Int. J. Approx. Reason..

Tree Augmented Naive Bayes for Regression Using Mixtures of Truncated Exponentials: Application to Higher Education Management

Antonio Salmerón, Antonio Fernández, María Morales, 2007, IDA.

Learning mixtures of truncated basis functions from data

Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, 2014, Int. J. Approx. Reason..

Construction of Fuzzy Measures over Product Spaces

Antonio Salmerón, Fernando Reche, María Morales, 2020, Mathematics.

An Experimental Comparison of Methods to Handle Missing Values in Environmental Datasets

Antonio Salmerón, A. D. Maldonado, Pedro A. Aguilera, 2016 .

Probability Tree Factorisation with Median Free Term

Irene Martínez, Carmelo Rodríguez, Antonio Salmerón, 2010, SMPS.

Mixtures of truncated basis functions

Rafael Rumí, Antonio Salmerón, Thomas D. Nielsen, 2012, Int. J. Approx. Reason..

Mixture of truncated exponentials in supervised classification: Case study for the naive bayes and averaged one-dependence estimators classifiers

José A. Gámez, Antonio Salmerón, Ana M. Martínez, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

Bayesian networks in environmental modelling

Rafael Rumí, Pedro Aguilera Aguilera, Antonio Salmerón, 2011, Environ. Model. Softw..

Answering queries in hybrid Bayesian networks using importance sampling

Rafael Rumí, Antonio Salmerón, Antonio Fernández, 2012, Decis. Support Syst..

A system for relevance analysis of performance indicators in higher education using Bayesian networks

Carmelo Rodríguez, Antonio Salmerón, Antonio Fernández, 2011, Knowledge and Information Systems.

Continuous Bayesian networks for probabilistic environmental risk mapping

Antonio Salmerón, Pedro A. Aguilera, A. D. Maldonado, 2016, Stochastic Environmental Research and Risk Assessment.

Inventory management with log-normal demand per unit time

Rafael Rumí, Antonio Salmerón, Barry R. Cobb, 2013, Comput. Oper. Res..

First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002 - Cuenca (Spain), Electronic Proceedings

José A. Gámez, Antonio Salmerón, 2002, Probabilistic Graphical Models.

Dynamic Importance Sampling Computation in Bayesian Networks

Serafín Moral, Antonio Salmerón, A. Salmerón, 2003, ECSQARU.

Importance Sampling in Bayesian Networks Using Antithetic Variables

Serafín Moral, Antonio Salmerón, A. Salmerón, 2001, ECSQARU.

Approximate probability propagation with mixtures of truncated exponentials

Rafael Rumí, Antonio Salmerón, A. Salmerón, 2007, Int. J. Approx. Reason..

Modeling Concept Drift: A Probabilistic Graphical Model Based Approach

Andrés R. Masegosa, Anders L. Madsen, Antonio Salmerón, 2015, IDA.

Requirement Engineering for a Small Project with Pre-Specified Scope

Andrés R. Masegosa, Sigve Hovda, Anders L. Madsen, 2014, NIK.

A Java Toolbox for Analysis of MassIve Data STreams using Probabilistic Graphical Models

Andrés R. Masegosa, Anders L. Madsen, Antonio Salmerón, 2016 .

Estimation of Species Richness Using Bayesian Networks

Rosa F. Ropero, Rafael Rumí, Pedro Aguilera Aguilera, 2015, CAEPIA.

Inference in Bayesian Networks with Recursive Probability Trees: Data Structure Definition and Operations

Antonio Salmerón, Andrés Cano, Cora B. Pérez-Ariza, 2013, Int. J. Intell. Syst..

Multivariate Imputation of Qualitative Missing Data Using Bayesian Networks

Antonio Salmerón, Vanessa Romero, A. Salmerón, 2004 .

Supervised classification using probabilistic decision graphs

Rafael Rumí, Antonio Salmerón, Jens Dalgaard Nielsen, 2009, Comput. Stat. Data Anal..

AMIDST: Analysis of MassIve Data STreams

Andrés R. Masegosa, Anders L. Madsen, Antonio Salmerón, 2015 .

Modelling and inference with Conditional Gaussian Probabilistic Decision Graphs

José A. Gámez, Antonio Salmerón, Jens Dalgaard Nielsen, 2012, Int. J. Approx. Reason..

InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy

Andrés R. Masegosa, Javier Cózar, Antonio Salmerón, 2020, Neurocomputing.

Penniless Propagation with Mixtures of Truncated Exponentials

Rafael Rumí, Antonio Salmerón, A. Salmerón, 2005, ECSQARU.

Practical Aspects of Solving Hybrid Bayesian Networks Containing Deterministic Conditionals

Prakash P. Shenoy, Rafael Rumí, Antonio Salmerón, 2015, Int. J. Intell. Syst..

Factorisation of Probability Trees and its Application to Inference in Bayesian Networks

Serafín Moral, Irene Martínez, Carmelo Rodríguez, 2002, Probabilistic Graphical Models.

Dynamic Bayesian modeling for risk prediction in credit operations

Andrés R. Masegosa, Anders L. Madsen, Antonio Salmerón, 2015, SCAI.

Parameter learning in MTE networks using incomplete data

Antonio Fernández, Antonio Salmerón, Thomas D. Nielsen, 2010 .

Maximum Likelihood Learning of Conditional MTE Distributions

Rafael Rumí, Antonio Salmerón, Thomas D. Nielsen, 2009, ECSQARU.

A survey on Bayesian network structure learning from data

Fabio Stella, Antonio Salmerón, Mauro Scanagatta, 2019, Progress in Artificial Intelligence.

Approximating Conditional MTE Distributions by Means of Mixed Trees

Serafín Moral, Rafael Rumí, Antonio Salmerón, 2003, ECSQARU.

Conditional Gaussian Probabilistic Decision Graphs

Antonio Salmerón, Jens Dalgaard Nielsen, 2010, FLAIRS Conference.

Probabilistic Models with Deep Neural Networks

Andrés R. Masegosa, Antonio Salmerón, Rafael Cabañas, 2019, Entropy.

Parallelisation of the PC Algorithm

Anders L. Madsen, Antonio Salmerón, Thomas D. Nielsen, 2015, CAEPIA.

A Review of Inference Algorithms for Hybrid Bayesian Networks

Rafael Rumí, Anders L. Madsen, Antonio Salmerón, 2018, J. Artif. Intell. Res..

Dynamic importance sampling in Bayesian networks based on probability trees

Serafín Moral, Antonio Salmerón, 2005, Int. J. Approx. Reason..

Some practical issues in inference in hybrid Bayesian networks with deterministic conditionals

Prakash P. Shenoy, Rafael Rumí, Antonio Salmerón, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

Guest editorial: new trends in probabilistic graphical models

José A. Gámez, Antonio Salmerón, 2004 .

Representing Canonical Models as Probability Trees

Antonio Salmerón, José del Sagrado, A. Salmerón, 2003, CAEPIA.

Estimating Mixtures of Truncated Exponentials from Data

Serafín Moral, Rafael Rumí, Antonio Salmerón, 2002, Probabilistic Graphical Models.

Recent Advances in Probabilistic Graphical Models

Concha Bielza, Serafín Moral, Antonio Salmerón, 2015, Int. J. Intell. Syst..

Aalborg Universitet Inference in hybrid Bayesian networks

Rafael Rumí, Antonio Salmerón, Thomas D. Nielsen, 2016 .

Operational Approach to General Fuzzy Measures

Antonio Salmerón, Fernando Reche, 2000, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Parameter estimation and model selection for mixtures of truncated exponentials

Rafael Rumí, Antonio Salmerón, Thomas D. Nielsen, 2010, Int. J. Approx. Reason..

Fast Factorisation of Probabilistic Potentials and its Application to Approximate Inference in Bayesian Networks

Antonio Salmerón, Andrés Cano, Cora B. Pérez-Ariza, 2012, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials

José A. Gámez, Rafael Rumí, Antonio Salmerón, 2006, Probabilistic Graphical Models.

Approximate Factorisation of Probability Trees

Serafín Moral, Irene Martínez, Carmelo Rodríguez, 2005, ECSQARU.

Continuous Bayesian networks for the estimation of species richness

Rosa F. Ropero, Rafael Rumí, Pedro Aguilera Aguilera, 2015, Progress in Artificial Intelligence.

Bayesian Network Models with Discrete and Continuous Variables

Rafael Rumí, Antonio Salmerón, Barry R. Cobb, 2007 .

Structural Learning of Bayesian Networks with Mixtures of Truncated Exponentials

Rafael Rumí, Antonio Salmerón, Vanessa Romero, 2004 .

New strategies for finding multiplicative decompositions of probability trees

Serafín Moral, Irene Martínez, Carmelo Rodríguez, 2013, Appl. Math. Comput..

Learning hybrid Bayesian networks using mixtures of truncated exponentials

Rafael Rumí, Antonio Salmerón, Vanessa Romero, 2006, Int. J. Approx. Reason..

Fast Factorization of Probability Trees and Its Application to Recursive Trees Learning

Antonio Salmerón, Andrés Cano, Cora B. Pérez-Ariza, 2010, SMPS.

Modeling Conditional Distributions of Continuous Variables in Bayesian Networks

Rafael Rumí, Antonio Salmerón, Barry R. Cobb, 2005, IDA.

Penniless propagation in join trees

Serafín Moral, Antonio Salmerón, Andrés Cano, 2000, Int. J. Intell. Syst..

Incremental Supervised Classification for the MTE Distribution: a Preliminary Study

Ildikó Flesch, Antonio Fernández, Antonio Salmerón, 2007 .

Advances in Bayesian Networks (Studies in Fuzziness and Soft Computing, V. 146)

Antonio Salmerón, Jose A. Gamez, Serafin Moral, 2004 .

Predicting Stock and Portfolio Returns Using Mixtures of Truncated Exponentials

Rafael Rumí, Antonio Salmerón, Barry R. Cobb, 2009, ECSQARU.

Probabilistic graphical models

José A. Gámez, Antonio Salmerón, A. Salmerón, 2003, Int. J. Intell. Syst..

Analyzing Uncertainty in Complex Socio-Ecological Networks

Pedro Aguilera Aguilera, Antonio Salmerón, A. D. Maldonado, 2020, Entropy.

A tool based on Bayesian networks for supporting geneticists in plant improvement by controlled pollination

José A. Gámez, Antonio Salmerón, Jens Dalgaard Nielsen, 2014, Int. J. Approx. Reason..

Structural-EM for learning PDG models from incomplete data

Rafael Rumí, Antonio Salmerón, Jens Dalgaard Nielsen, 2010, Int. J. Approx. Reason..

Selective Naive Bayes for Regression Based on Mixtures of Truncated Exponentials

Carmelo Rodríguez, Antonio Salmerón, María Morales, 2007, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Supervised Classification Using Hybrid Probabilistic Decision Graphs

Rafael Rumí, Antonio Salmerón, Antonio Fernández, 2014, Probabilistic Graphical Models.

Data clustering using hidden variables in hybrid Bayesian networks

José A. Gámez, Rafael Rumí, Antonio Salmerón, 2014, Progress in Artificial Intelligence.

BayesChess: A computer chess program based on Bayesian networks

Antonio Salmerón, Antonio Fernández, 2008, Pattern Recognit. Lett..

Analyzing concept drift: A case study in the financial sector

Andrés R. Masegosa, Antonio Salmerón, Ana M. Martínez, 2020, Intell. Data Anal..

Mixtures of Truncated Exponentials in Hybrid Bayesian Networks

Serafín Moral, Rafael Rumí, Antonio Salmerón, 2001, ECSQARU.

Advances in Bayesian networks

José A. Gámez, Serafín Moral, Antonio Salmerón, 2004 .

Learning Bayesian Networks for Regression from Incomplete Databases

Antonio Salmerón, Jens Dalgaard Nielsen, Antonio Fernández, 2010, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Continuous Bayesian Networks vs. Other Methods for Regression in Environmental Modelling

Rosa F. Ropero, Rafael Rumí, Antonio Salmerón, 2015 .

Analysis of massive data streams using R and AMIDST

Anders L. Madsen, Antonio Salmerón, 2015 .

A Soft Clustering Approach to Detect Socio-Ecological Landscape Boundaries Using Bayesian Networks

Rosa F. Ropero, Rafael Rumí, Antonio Salmerón, 2021, Agronomy.

Estimating mixtures of truncated exponentials in hybrid bayesian networks

Serafín Moral, Rafael Rumí, Antonio Salmerón, 2006 .

Parallelisation of the PC Algorithm

Anders L. Madsen, Antonio Salmerón, Thomas D. Nielsen, 2015, CAEPIA.

Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions

Rafael Rumí, Antonio Salmerón, Thomas D. Nielsen, 2012, PGM 2012.

Predicción del valor genético en ovejas de raza manchega usando técnicas de aprendizaje automático

José A. Gámez, Antonio Salmerón, 2005 .

Selective Naive Bayes Predictor with Mixtures of Truncated Exponentials

Antonio Salmerón, Mar ´ õa Morales, Carmelo Rodr ´ õguez, 2006 .

Penniless propagation in join trees

Serafín Moral, Antonio Salmerón, Andrés Cano, 2000 .