Articles 2014

• Anton-Sanchez, L., C. Bielza, A. Merchán-Pérez, J. R. Rodríguez, J. DeFelipe, and P. Larrañaga, “Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis“, Frontiers in Neuroanatomy, vol. 8, pp. Article 85, 2014, Also available in the ebook: http://www.frontiersin.org/books/Quantitative_Analysis_of_Neuroanatomy/829. 

• Bielza, C., and P. Larrañaga, “Bayesian networks in neuroscience: A survey“, Frontiers in Computational Neuroscience, vol. 8, pp. Article 131, 2014. 

• Bielza, C., R. Benavides-Piccione, P. L. Lopez-Cruz, P. Larrañaga, and J. DeFelipe, “Branching angles of pyramidal cell dendrites follow common geometrical design principles in different cortical areas“, Scientific Reports, vol. 4, pp. Article 5909, 2014. 

• Bielza, C., and P. Larrañaga, “Discrete Bayesian Network Classifiers: A Survey“, ACM Computing Surveys, vol. 47, no. 1, pp. Article 5, 2014. 

• Borchani, H., C. Bielza, P. Martínez-Martín, and P. Larrañaga, “Predicting EQ-5D from the Parkinson’s disease questionnaire PDQ-8 using multi-dimensional Bayesian network classifiers“, Biomedical Engineering: Applications, Basis and Communications (no JCR) , vol. 26, no. 1, pp. 1450015, 2014. 

• Guerra, L., C. Bielza, V. Robles, and P. Larrañaga, “Semi-supervised projected model-based clustering“, Data Mining and Knowledge Discovery, vol. 28, no. 4, pp. 882-917, 2014. 

• Ibañez, A., C. Bielza, and P. Larrañaga, “Cost-sensitive selective naive Bayes classifiers for predicting the increase of the h-index for scientific journals“, Neurocomputing, vol. 135, no. 5, pp. 45-52, 2014. 

• Karshenas, H., R. Santana, C. Bielza, and P. Larrañaga, “Multi-objective estimation of distribution algorithm based on joint modeling of objectives and variables“, IEEE Transactions on Evolutionary Computation, vol. 18, no. 4, pp. 519-542, 2014. 

• Lopez-Cruz, P. L., C. Bielza, and P. Larrañaga, “Learning mixtures of polynomials of multidimensional probability densities from data using B-spline interpolation“, International Journal of Approximate Reasoning, vol. 55, no. 4, pp. 989–1010, 2014. 

• Lopez-Cruz, P. L., P. Larrañaga, , and C. Bielza, “Bayesian network modeling of the consensus between experts: An application to neuron classification“, International Journal of Approximate Reasoning, vol. 55, no. 1, pp. 3-22, 2014. 

• Merchán-Pérez, A., R. Rodríguez, S. González, V. Robles, J. DeFelipe, P. Larrañaga, and C. Bielza, “Three-dimensional spatial distribution of synapses in the neocortex: A dual-beam electron microscopy study”, Cerebral Cortex, vol. 24, pp. 1579-1588, 2014. 

• Mihaljevic, B., C. Bielza, R. Benavides-Piccione, J. DeFelipe, and P. Larrañaga, “Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty“, Frontiers in Computional Neuroscience, vol. 8, pp. Article 150, 2014. 

• Morales, J., R. Benavides-Piccione, M. Dar, I. Fernaud, A. Rodríguez, L. Anton-Sanchez, C. Bielza, P. Larrañaga, J. DeFelipe, and R. Yuste, “Random positions of dendritic spines in human cerebral cortex“, Journal of Neuroscience, vol. 34, no. 30, pp. 10078-10084, 2014. 

• Read, J., C. Bielza, and P. Larrañaga, “Multi-dimensional classification with super-classes“, IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 7, pp. 1720-1733, 2014. 

• Sucar, E., C. Bielza, E. F. Morales, P. Hernandez-Leal, J. H. Zaragoza, and P. Larrañaga, “Multi-label Classification with Bayesian Network-based Chain Classifiers“, Pattern Recognition Letters, vol. 41, pp. 14-22, 2014.