A Monte Carlo algorithm for probabilistic propagation in belief networks based on importance sampling and stratified simulation techniques. - Luis D. Hernández; Serafín Moral; Antonio Salmerón (Int. J. Approx. Reason., 1998)

A Monte Carlo Algorithm for Combining Dempster-Shafer Belief Based on Approximate Pre-computation. - Serafín Moral; Antonio Salmerón (ESCQARU, 1999)

Towards an Operational Interpretation of Fuzzy Measures. - Fernando Reche; Antonio Salmerón (ISIPTA, 1999)

Penniless propagation in join trees. - Andrés Cano; Serafín Moral; Antonio Salmerón (Int. J. Intell. Syst., 2000)

Operational Approach to General Fuzzy Measures. - Fernando Reche; Antonio Salmerón (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2000)

Mixtures of Truncated Exponentials in Hybrid Bayesian Networks. - Serafín Moral; Rafael Rumí; Antonio Salmerón (ECSQARU, 2001)

Importance Sampling in Bayesian Networks Using Antithetic Variables. - Antonio Salmerón; Serafín Moral (ECSQARU, 2001)

Factorisation of Probability Trees and its Application to Inference in Bayesian Networks. - Irene Martínez; Serafín Moral; Carmelo Rodríguez; Antonio Salmerón (Probabilistic Graphical Models, 2002)

Estimating Mixtures of Truncated Exponentials from Data. - Serafín Moral; Rafael Rumí; Antonio Salmerón (Probabilistic Graphical Models, 2002)

Different strategies to approximate probability trees in penniless propagation. - Andrés Cano; Serafín Moral; Antonio Salmerón (Inteligencia Artif., 2002)

Lazy evaluation in penniless propagation over join trees. - Andrés Cano; Serafín Moral; Antonio Salmerón (Networks, 2002)

Representing Canonical Models as Probability Trees. - José del Sagrado; Antonio Salmerón (CAEPIA, 2003)

Approximating Conditional MTE Distributions by Means of Mixed Trees. - Serafín Moral; Rafael Rumí; Antonio Salmerón (ECSQARU, 2003)

Dynamic Importance Sampling Computation in Bayesian Networks. - Serafín Moral; Antonio Salmerón (ECSQARU, 2003)

Novel strategies to approximate probability trees in penniless propagation. - Andrés Cano; Serafín Moral; Antonio Salmerón (Int. J. Intell. Syst., 2003)

Probabilistic graphical models. - José A. Gámez 001; Antonio Salmerón (Int. J. Intell. Syst., 2003)

Approximate Factorisation of Probability Trees. - Irene Martínez; Serafín Moral; Carmelo Rodríguez; Antonio Salmerón (ECSQARU, 2005)

Penniless Propagation with Mixtures of Truncated Exponentials. - Rafael Rumí; Antonio Salmerón (ECSQARU, 2005)

Modeling Conditional Distributions of Continuous Variables in Bayesian Networks. - Barry R. Cobb; Rafael Rumí; Antonio Salmerón (IDA, 2005)

Dynamic importance sampling in Bayesian networks based on probability trees. - Serafín Moral; Antonio Salmerón (Int. J. Approx. Reason., 2005)

Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials. - José A. Gámez 001; Rafael Rumí; Antonio Salmerón (Probabilistic Graphical Models, 2006)

Dynamic importance sampling in Bayesian networks using factorisation of probability trees. - Irene Martínez; Carmelo Rodríguez; Antonio Salmerón (Probabilistic Graphical Models, 2006)

Special issue on PGM'04: Second European workshop on probabilistic graphical models 2004. - Peter J. F. Lucas; José A. Gámez 001; Antonio Salmerón (Int. J. Approx. Reason., 2006)

Learning hybrid Bayesian networks using mixtures of truncated exponentials. - Vanessa Romero; Rafael Rumí; Antonio Salmerón (Int. J. Approx. Reason., 2006)

Tree Augmented Naive Bayes for Regression Using Mixtures of Truncated Exponentials: Application to Higher Education Management. - Antonio Fernández 002; María Morales; Antonio Salmerón (IDA, 2007)

Approximate probability propagation with mixtures of truncated exponentials. - Rafael Rumí; Antonio Salmerón (Int. J. Approx. Reason., 2007)

Selective Naive Bayes for Regression Based on Mixtures of Truncated Exponentials. - María Morales; Carmelo Rodríguez; Antonio Salmerón (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2007)

Extension of Bayesian Network Classifiers to Regression Problems. - Antonio Fernández 002; Antonio Salmerón (IBERAMIA, 2008)

BayesChess: A computer chess program based on Bayesian networks. - Antonio Fernández 002; Antonio Salmerón (Pattern Recognit. Lett., 2008)

Predicting Stock and Portfolio Returns Using Mixtures of Truncated Exponentials. - Barry R. Cobb; Rafael Rumí; Antonio Salmerón (ECSQARU, 2009)

Maximum Likelihood Learning of Conditional MTE Distributions. - Helge Langseth; Thomas D. Nielsen; Rafael Rumí; Antonio Salmerón (ECSQARU, 2009)

Supervised classification using probabilistic decision graphs. - Jens Dalgaard Nielsen; Rafael Rumí; Antonio Salmerón (Comput. Stat. Data Anal., 2009)

Inference in hybrid Bayesian networks. - Helge Langseth; Thomas D. Nielsen; Rafael Rumí; Antonio Salmerón (Reliab. Eng. Syst. Saf., 2009)

Conditional Gaussian Probabilistic Decision Graphs. - Jens Dalgaard Nielsen; Antonio Salmerón Cerdán (FLAIRS, 2010)

Fast Factorization of Probability Trees and Its Application to Recursive Trees Learning. - Andrés Cano; Manuel Gómez-Olmedo; Cora B. Pérez-Ariza; Antonio Salmerón (SMPS, 2010)

Probability Tree Factorisation with Median Free Term. - Irene Martínez; Carmelo Rodríguez; Antonio Salmerón (SMPS, 2010)

Parameter estimation and model selection for mixtures of truncated exponentials. - Helge Langseth; Thomas D. Nielsen; Rafael Rumí; Antonio Salmerón (Int. J. Approx. Reason., 2010)

Structural-EM for learning PDG models from incomplete data. - Jens Dalgaard Nielsen; Rafael Rumí; Antonio Salmerón (Int. J. Approx. Reason., 2010)

Learning Bayesian Networks for Regression from Incomplete Databases. - Antonio Fernández 002; Jens Dalgaard Nielsen; Antonio Salmerón (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2010)

Mixture of truncated exponentials in supervised classification: Case study for the naive bayes and averaged one-dependence estimators classifiers. - M. Julia Flores; José A. Gámez 001; Ana M. Martínez; Antonio Salmerón (ISDA, 2011)

Some practical issues in inference in hybrid Bayesian networks with deterministic conditionals. - Prakash P. Shenoy; Rafael Rumí; Antonio Salmerón (ISDA, 2011)

Bayesian networks in environmental modelling. - Pedro Aguilera Aguilera; Antonio Fernández 002; Rosa Fernández; Rafael Rumí; Antonio Salmerón (Environ. Model. Softw., 2011)

A system for relevance analysis of performance indicators in higher education using Bayesian networks. - Antonio Fernández 002; María Morales; Carmelo Rodríguez; Antonio Salmerón (Knowl. Inf. Syst., 2011)

Moments and associated measures of copulas with fractal support. - Enrique de Amo; Manuel Díaz Carrillo; Juan Fernández-Sánchez; Antonio Salmerón (Appl. Math. Comput., 2012)

Answering queries in hybrid Bayesian networks using importance sampling. - Antonio Fernández 002; Rafael Rumí; Antonio Salmerón (Decis. Support Syst., 2012)

Learning recursive probability trees from probabilistic potentials. - Andrés Cano; Manuel Gómez-Olmedo; Serafín Moral; Cora B. Pérez-Ariza; Antonio Salmerón (Int. J. Approx. Reason., 2012)

Mixtures of truncated basis functions. - Helge Langseth; Thomas D. Nielsen; Rafael Rumí; Antonio Salmerón (Int. J. Approx. Reason., 2012)

Modelling and inference with Conditional Gaussian Probabilistic Decision Graphs. - Jens Dalgaard Nielsen; José A. Gámez 001; Antonio Salmerón (Int. J. Approx. Reason., 2012)

Fast Factorisation of Probabilistic Potentials and its Application to Approximate Inference in Bayesian Networks. - Andrés Cano; Manuel Gómez-Olmedo; Cora B. Pérez-Ariza; Antonio Salmerón (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2012)

On Using the PC Algorithm for Learning Continuous Bayesian Networks: An Experimental Analysis. - Antonio Fernández 002; Inmaculada Pérez-Bernabé; Antonio Salmerón (CAEPIA, 2013)

Learning Recursive Probability Trees from Data. - Andrés Cano; Manuel Gómez-Olmedo; Serafín Moral; Cora Beatriz Pérez-Ariza; Antonio Salmerón (CAEPIA, 2013)

Incorporating Prior Knowledge when Learning Mixtures of Truncated Basis Functions from Data. - Antonio Fernández 002; Inmaculada Pérez-Bernabé; Rafael Rumí; Antonio Salmerón (SCAI, 2013)

New strategies for finding multiplicative decompositions of probability trees. - Irene Martínez; Serafín Moral; Carmelo Rodríguez; Antonio Salmerón (Appl. Math. Comput., 2013)

Inventory management with log-normal demand per unit time. - Barry R. Cobb; Rafael Rumí; Antonio Salmerón (Comput. Oper. Res., 2013)

Inference in Bayesian Networks with Recursive Probability Trees: Data Structure Definition and Operations. - Andrés Cano; Manuel Gómez-Olmedo; Serafín Moral; Cora B. Pérez-Ariza; Antonio Salmerón (Int. J. Intell. Syst., 2013)

Requirement Engineering for a Small Project with Pre-Specified Scope. - Thomas D. Nielsen; Sigve Hovda; Antonio Fernández 002; Helge Langseth; Anders L. Madsen; Andrés R. Masegosa; Antonio Salmerón (NIK, 2014)

Supervised Classification Using Hybrid Probabilistic Decision Graphs. - Antonio Fernández 002; Rafael Rumí; José del Sagrado; Antonio Salmerón (Probabilistic Graphical Models, 2014)

A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs. - Anders L. Madsen; Frank Jensen; Antonio Salmerón; Martin Karlsen; Helge Langseth; Thomas D. Nielsen (Probabilistic Graphical Models, 2014)

Learning mixtures of truncated basis functions from data. - Helge Langseth; Thomas D. Nielsen; Inmaculada Pérez-Bernabé; Antonio Salmerón (Int. J. Approx. Reason., 2014)

A tool based on Bayesian networks for supporting geneticists in plant improvement by controlled pollination. - Jens Dalgaard Nielsen; Antonio Salmerón; José A. Gámez 001 (Int. J. Approx. Reason., 2014)

Data clustering using hidden variables in hybrid Bayesian networks. - Antonio Fernández 002; José A. Gámez 001; Rafael Rumí; Antonio Salmerón (Prog. Artif. Intell., 2014)

Parallelisation of the PC Algorithm. - Anders L. Madsen; Frank Jensen; Antonio Salmerón; Helge Langseth; Thomas D. Nielsen (CAEPIA, 2015)

Estimation of Species Richness Using Bayesian Networks. - Ana D. Maldonado; Rosa F. Ropero; Pedro Aguilera Aguilera; Rafael Rumí; Antonio Salmerón (CAEPIA, 2015)

Parallel Importance Sampling in Conditional Linear Gaussian Networks. - Antonio Salmerón; Darío Ramos-López; Hanen Borchani; Ana M. Martínez; Andrés R. Masegosa; Antonio Fernández 002; Helge Langseth; Anders L. Madsen; Thomas D. Nielsen (CAEPIA, 2015)

Learning Conditional Distributions Using Mixtures of Truncated Basis Functions. - Inmaculada Pérez-Bernabé; Antonio Salmerón; Helge Langseth (ECSQARU, 2015)

MPE Inference in Conditional Linear Gaussian Networks. - Antonio Salmerón; Rafael Rumí; Helge Langseth; Anders L. Madsen; Thomas D. Nielsen (ECSQARU, 2015)

Modeling Concept Drift: A Probabilistic Graphical Model Based Approach. - Hanen Borchani; Ana M. Martínez; Andrés R. Masegosa; Helge Langseth; Thomas D. Nielsen; Antonio Salmerón; Antonio Fernández 002; Anders L. Madsen; Ramón Sáez (IDA, 2015)

Dynamic Bayesian modeling for risk prediction in credit operations. - Hanen Borchani; Ana M. Martínez; Andrés R. Masegosa; Helge Langseth; Thomas D. Nielsen; Antonio Salmerón; Antonio Fernández 002; Anders L. Madsen; Ramón Sáez (SCAI, 2015)

Recent Advances in Probabilistic Graphical Models. - Concha Bielza; Serafín Moral; Antonio Salmerón (Int. J. Intell. Syst., 2015)

Practical Aspects of Solving Hybrid Bayesian Networks Containing Deterministic Conditionals. - Prakash P. Shenoy; Rafael Rumí; Antonio Salmerón (Int. J. Intell. Syst., 2015)

Continuous Bayesian networks for the estimation of species richness. - Ana D. Maldonado; Rosa F. Ropero; Pedro Aguilera Aguilera; Rafael Rumí; Antonio Salmerón (Prog. Artif. Intell., 2015)

Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs. - Antonio Salmerón; Anders L. Madsen; Frank Jensen; Helge Langseth; Thomas D. Nielsen; Darío Ramos-López; Ana M. Martínez; Andrés R. Masegosa (ECAI, 2016)

Financial Data Analysis with PGMs Using AMIDST. - Rafael Cabañas 001; Ana M. Martínez; Andrés R. Masegosa; Darío Ramos-López; Antonio Salmerón; Thomas D. Nielsen; Helge Langseth; Anders L. Madsen (ICDM Workshops, 2016)

d-VMP: Distributed Variational Message Passing. - Andrés R. Masegosa; Ana M. Martínez; Helge Langseth; Thomas D. Nielsen; Antonio Salmerón; Darío Ramos-López; Anders L. Madsen (Probabilistic Graphical Models, 2016)

Scalable MAP inference in Bayesian networks based on a Map-Reduce approach. - Darío Ramos-López; Antonio Salmerón; Rafael Rumí; Ana M. Martínez; Thomas D. Nielsen; Andrés R. Masegosa; Helge Langseth; Anders L. Madsen (Probabilistic Graphical Models, 2016)

Parameter learning in hybrid Bayesian networks using prior knowledge. - Inmaculada Pérez-Bernabé; Antonio Fernández 002; Rafael Rumí; Antonio Salmerón (Data Min. Knowl. Discov., 2016)

Modeling zero-inflated explanatory variables in hybrid Bayesian network classifiers for species occurrence prediction. - Ana D. Maldonado; Pedro Aguilera Aguilera; Antonio Salmerón (Environ. Model. Softw., 2016)

Bayesian Models of Data Streams with Hierarchical Power Priors. - Andrés R. Masegosa; Thomas D. Nielsen; Helge Langseth; Darío Ramos-López; Antonio Salmerón; Anders L. Madsen (ICML, 2017)

Scaling up Bayesian variational inference using distributed computing clusters. - Andrés R. Masegosa; Ana M. Martínez; Helge Langseth; Thomas D. Nielsen; Antonio Salmerón; Darío Ramos-López; Anders L. Madsen (Int. J. Approx. Reason., 2017)

A parallel algorithm for Bayesian network structure learning from large data sets. - Anders L. Madsen; Frank Jensen; Antonio Salmerón; Helge Langseth; Thomas D. Nielsen (Knowl. Based Syst., 2017)

MAP inference in dynamic hybrid Bayesian networks. - Darío Ramos-López; Andrés R. Masegosa; Ana M. Martínez; Antonio Salmerón; Thomas D. Nielsen; Helge Langseth; Anders L. Madsen (Prog. Artif. Intell., 2017)

Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks. - Darío Ramos-López; Andrés R. Masegosa; Antonio Salmerón; Rafael Rumí; Helge Langseth; Thomas D. Nielsen; Anders L. Madsen (Int. J. Approx. Reason., 2018)

A Review of Inference Algorithms for Hybrid Bayesian Networks. - Antonio Salmerón; Rafael Rumí; Helge Langseth; Thomas D. Nielsen; Anders L. Madsen (J. Artif. Intell. Res., 2018)

Prediction of a complex system with few data: Evaluation of the effect of model structure and amount of data with dynamic bayesian network models. - Ana D. Maldonado; Laura Uusitalo; Allan Tucker; Thorsten Blenckner; Pedro Aguilera Aguilera; Antonio Salmerón (Environ. Model. Softw., 2019)

InferPy: Probabilistic modeling with Tensorflow made easy. - Rafael Cabañas 001; Antonio Salmerón; Andrés R. Masegosa (Knowl. Based Syst., 2019)

AMIDST: A Java toolbox for scalable probabilistic machine learning. - Andrés R. Masegosa; Ana M. Martínez; Darío Ramos-López; Rafael Cabañas 001; Antonio Salmerón; Helge Langseth; Thomas D. Nielsen; Anders L. Madsen (Knowl. Based Syst., 2019)

A survey on Bayesian network structure learning from data. - Mauro Scanagatta; Antonio Salmerón; Fabio Stella (Prog. Artif. Intell., 2019)

Probabilistic Graphical Models with Neural Networks in InferPy. - Rafael Cabañas 001; Javier Cózar; Antonio Salmerón; Andrés R. Masegosa (PGM, 2020)

Analyzing Uncertainty in Complex Socio-Ecological Networks. - Ana D. Maldonado; María Morales; Pedro Aguilera Aguilera; Antonio Salmerón (Entropy, 2020)

Analyzing concept drift: A case study in the financial sector. - Andrés R. Masegosa; Ana M. Martínez; Darío Ramos-López; Helge Langseth; Thomas D. Nielsen; Antonio Salmerón (Intell. Data Anal., 2020)

InferPy: Probabilistic modeling with deep neural networks made easy. - Javier Cózar; Rafael Cabañas 001; Antonio Salmerón; Andrés R. Masegosa (Neurocomputing, 2020)

Comparing two multinomial samples using hierarchical Bayesian models. - Andrés R. Masegosa; Antonio Torres; María Morales; Antonio Salmerón (Prog. Artif. Intell., 2020)

MoTBFs: An R Package for Learning Hybrid Bayesian Networks Using Mixtures of Truncated Basis Functions. - Inmaculada Pérez-Bernabé; Ana D. Maldonado; Antonio Salmerón; Thomas D. Nielsen (R J., 2020)

Probabilistic Models with Deep Neural Networks. - Andrés R. Masegosa; Rafael Cabañas 001; Helge Langseth; Thomas D. Nielsen; Antonio Salmerón (Entropy, 2021)

A Reparameterization of Mixtures of Truncated Basis Functions and its Applications. - Antonio Salmerón; Helge Langseth; Andrés R. Masegosa; Thomas D. Nielsen (PGM, 2022)

Bayesian Network analysis of software logs for data-driven software maintenance. - Santiago del Rey; Silverio Martínez-Fernández; Antonio Salmerón (IET Softw., 2023)

A Divide and Conquer Approach for Solving Structural Causal Models. - Anna Rodum Bjøru; Rafael Cabañas 001; Helge Langseth; Antonio Salmerón (PGM, 2024)

Counterfactual Reasoning with Probabilistic Graphical Models for Analyzing Socioecological Systems. - Rafael Cabañas 001; Ana D. Maldonado; María Morales; Pedro Aguilera Aguilera; Antonio Salmerón (CoRR, 2024)

How do Machine Learning Models Change? - Joel Castaño; Rafael Cabañas 001; Antonio Salmerón; David Lo 001; Silverio Martínez-Fernández (CoRR, 2024)

Replication Package for 'How do Machine Learning Models Change?'. - Joel Castaño Fernández; Rafael Cabañas 001; Antonio Salmerón; David Lo 001; Silverio Martínez-Fernández (Zenodo, 2024)

Replication Package for 'How do Machine Learning Models Change?'. - Joel Castaño Fernández; Rafael Cabañas 001; Antonio Salmerón; David Lo 001; Silverio Martínez-Fernández (Zenodo, 2024)

Bayesian networks for causal analysis in socioecological systems. - Rafael Cabañas 001; Ana D. Maldonado; María Morales; Pedro Aguilera Aguilera; Antonio Salmerón (Ecol. Informatics, 2025)

Divide and conquer for causal computation. - Anna Rodum Bjøru; Rafael Cabañas 001; Helge Langseth; Antonio Salmerón (Int. J. Approx. Reason., 2025)