Publicaciones (71) Publicaciones de ANDRÉS CANO UTRERA

2023

  1. Imprecise probabilistic models based on hierarchical intervals

    Information Sciences, Vol. 638

  2. The Twelfth International Symposium on Imprecise Probabilities: Theories and Applications (ISIPTA-21)

    International Journal of Approximate Reasoning

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. A linear programming based approach for evaluating interval-valued influence diagrams

    XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España

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

    Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications: 17th International Conference, IPMU 2018, Cádiz, Spain, June 11-15, 2018, Proceedings, Part III

  3. 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)

  2. Evaluating interval-valued influence diagrams

    International Journal of Approximate Reasoning, Vol. 80, pp. 393-411

2016

  1. Improvements to Variable Elimination and Symbolic Probabilistic Inference for evaluating Influence Diagrams

    International Journal of Approximate Reasoning, Vol. 70, pp. 13-35

  2. Using binary trees for the evaluation of influence diagrams

    International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, Vol. 24, Núm. 1, pp. 59-89

2015

  1. An extended approach to learning recursive probability trees from data

    International Journal of Intelligent Systems, Vol. 30, Núm. 3, pp. 355-383

  2. Máster en Ciencia de Datos e Ingeniería de Computadores: una apuesta por la formación especializada en el sector de las TIC

    Enseñanza y aprendizaje de ingeniería de computadores: Revista de Experiencias Docentes en Ingeniería de Computadores, Núm. 5, pp. 5-16

  3. Variable elimination for interval-valued influence diagrams

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