Publicaciones en las que colabora con ANDRÉS CANO UTRERA (47)

2023

  1. Imprecise probabilistic models based on hierarchical intervals

    Information Sciences, Vol. 638

2022

  1. Using Value-Based Potentials for Making Approximate Inference on Probabilistic Graphical Models

    Mathematics, Vol. 10, Núm. 14

2021

  1. Computation of Kullback–Leibler divergence in Bayesian networks

    Entropy, Vol. 23, Núm. 9

  2. ISIPTA 2021: Preface

    Proceedings of Machine Learning Research

  3. Value-based potentials: Exploiting quantitative information regularity patterns in probabilistic graphical models

    International Journal of Intelligent Systems, Vol. 36, Núm. 11, pp. 6913-6943

2020

  1. Learning sets of bayesian networks

    Communications in Computer and Information Science

  2. MPE Computation in Bayesian Networks Using Mini-Bucket and Probability Trees Approximation

    International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, Vol. 28, Núm. 5, pp. 785-805

2019

  1. A Bayesian approach to abrupt concept drift

    Knowledge-Based Systems, Vol. 185

  2. Combining gene expression data and prior knowledge for inferring gene regulatory networks via Bayesian networks using structural restrictions

    Statistical Applications in Genetics and Molecular Biology, Vol. 18, Núm. 3

2018

  1. Virtual subconcept drift detection in discrete data using probabilistic graphical models

    Communications in Computer and Information Science

2017

  1. Estimating conditional probabilities by mixtures of low order conditional distributions

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2014

  1. Extended probability trees for probabilistic graphical models

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8754, pp. 113-128

  2. Heuristic algorithmsfor the triangulation of graphs

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 945, pp. 98-107

2013

  1. Inference in Bayesian networks with recursive probability trees: Data structure definition and operations

    International Journal of Intelligent Systems, Vol. 28, Núm. 7, pp. 623-647

  2. Learning recursive probability trees from data

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Locally averaged Bayesian Dirichlet metrics for learning the structure and the parameters of Bayesian networks

    International Journal of Approximate Reasoning

2012

  1. Learning recursive probability trees from probabilistic potentials

    International Journal of Approximate Reasoning

2011

  1. A memory efficient semi-Naive Bayes classifier with grouping of cases

    Intelligent Data Analysis, Vol. 15, Núm. 3, pp. 299-318

  2. A method for integrating expert knowledge when learning bayesian networks from data

    IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. 41, Núm. 5, pp. 1382-1394

  3. Approximate inference in Bayesian networks using binary probability trees

    International Journal of Approximate Reasoning