HODE: Hidden One-Dependence Estimator. - M. Julia Flores; José A. Gámez 001; Ana M. Martínez; José M. Puerta (ECSQARU, 2009)

GAODE and HAODE: two proposals based on AODE to deal with continuous variables. - M. Julia Flores; José A. Gámez 001; Ana M. Martínez; José M. Puerta (ICML, 2009)

Towards a More Expressive Model for Dynamic Classification. - Shengtong Zhong; Ana M. Martínez; Thomas D. Nielsen; Helge Langseth (FLAIRS, 2010)

Analyzing the Impact of the Discretization Method When Comparing Bayesian Classifiers. - M. Julia Flores; José A. Gámez 001; Ana M. Martínez; José M. Puerta (IEA/AIE (1), 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)

Handling numeric attributes when comparing Bayesian network classifiers: does the discretization method matter? - M. Julia Flores; José A. Gámez 001; Ana M. Martínez; José M. Puerta (Appl. Intell., 2011)

Non-Disjoint Discretization for Aggregating One-Dependence Estimator Classifiers. - Ana M. Martínez; Geoffrey I. Webb; M. Julia Flores; José A. Gámez 001 (HAIS (2), 2012)

Highly Scalable Attribute Selection for Averaged One-Dependence Estimators. - Shenglei Chen; Ana M. Martínez; Geoffrey I. Webb (PAKDD (2), 2014)

Domains of competence of the semi-naive Bayesian network classifiers. - M. Julia Flores; José A. Gámez 001; Ana M. Martínez (Inf. Sci., 2014)

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)

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)

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)

Probabilistic Graphical Models on Multi-Core CPUs Using Java 8. - Andrés R. Masegosa; Ana M. Martínez; Hanen Borchani (IEEE Comput. Intell. Mag., 2016)

Scalable Learning of Bayesian Network Classifiers. - Ana M. Martínez; Geoffrey I. Webb; Shenglei Chen; Nayyar Abbas Zaidi (J. Mach. Learn. Res., 2016)

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)

Selective AnDE for large data learning: a low-bias memory constrained approach. - Shenglei Chen; Ana M. Martínez; Geoffrey I. Webb; Limin Wang 007 (Knowl. Inf. 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)

Sample-Based Attribute Selective An DE for Large Data. - Shenglei Chen; Ana M. Martínez; Geoffrey I. Webb; Limin Wang 007 (IEEE Trans. Knowl. Data Eng., 2017)

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)

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)