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Cabañas de Paz, Rafael Author

InferPy: Probabilistic modeling with deep neural networks made easy

  • Cózar J.
  • Cabañas R.
  • Salmerón A.
  • Masegosa A.R.

Neurocomputing - 20/11/2020

10.1016/j.neucom.2020.07.117

Cite count: 2 (Web of Science) 2 (Scopus)
  • JCR Quartile: Q1 (2020)
  • SJR Quartile: Q1
  • JCR Impact Factor: 5.719 (2023)
  • Category normalized Impact: 0.092 (2020)
  • CiteScore: 9.8 (2020)
  • SJR: 1.085 (2020
  • SNIP: 2.108 (2020
  • JCR 5-year Impact Factor: 4.986
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Cognitive Neuroscience (Q1); Computer Science Applications (Q1); Artificial Intelligence (Q1)
Open Access

AMIDST: A Java toolbox for scalable probabilistic machine learning

  • Masegosa A.
  • Martínez A.
  • Ramos-López D.
  • Cabañas R.
  • Salmerón A.
  • Langseth H.
  • Nielsen T.
  • Madsen A.
... View more Collapse

Knowledge-Based Systems - 1/01/2019

10.1016/j.knosys.2018.09.019

Cite count: 7 (Web of Science) 7 (Scopus)
  • JCR Quartile: Q1 (2019)
  • SJR Quartile: Q1
  • JCR Impact Factor: 5.921 (2023)
  • Category normalized Impact: 0.384 (2019)
  • CiteScore: 11.3 (2020)
  • SJR: 1.754 (2019
  • SNIP: 2.828 (2019
  • JCR 5-year Impact Factor: 6.075
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q1); Information Systems and Management (Q1); Management Information Systems (Q1); Software (Q1)
Open Access

InferPy: Probabilistic modeling with Tensorflow made easy

  • Cabañas R.
  • Salmerón A.
  • Masegosa A.

Knowledge-Based Systems - 15/03/2019

10.1016/j.knosys.2018.12.030

Cite count: 6 (Web of Science) 3 (Scopus)
  • JCR Quartile: Q1 (2019)
  • SJR Quartile: Q1
  • JCR Impact Factor: 5.921 (2023)
  • Category normalized Impact: 0.298 (2019)
  • CiteScore: 11.3 (2020)
  • SJR: 1.754 (2019
  • SNIP: 2.828 (2019
  • JCR 5-year Impact Factor: 6.075
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q1); Information Systems and Management (Q1); Management Information Systems (Q1); Software (Q1)

Using binary trees for the evaluation of influence diagrams

  • Cabañas R.
  • Gómez-Olmedo M.
  • Cano A.

International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems - 1/2/2016

10.1142/s0218488516500045

Cite count: 4 (Web of Science) 2 (Scopus)
  • SJR Quartile: Q2
  • JCR Impact Factor: 1.214 (2016)
  • CiteScore: 2.5 (2020)
  • SJR: 0.591 (2016
  • SNIP: 0.762 (2016
  • JCR 5-year Impact Factor: 1.232
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q2); Control and Systems Engineering (Q2); Information Systems (Q2); Software (Q2)

Value‐based potentials: Exploiting quantitative information regularity patterns in probabilistic graphical models

  • Manuel Gómez‐Olmedo
  • Rafael Cabañas
  • Andrés Cano
  • Serafı́n Moral
  • Ofelia P. Retamero

International Journal of Intelligent Systems - 26/11/2021

10.1002/int.22573

Cite count: 1 (Web of Science)
  • JCR Quartile: Q2 (2021)
  • JCR Impact Factor: 8.993 (2022)
  • Category normalized Impact: 0.104 (2021)
  • JCR 5-year Impact Factor: 8.926
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Open Access

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

  • Cabañas R.
  • Cano A.
  • Gómez-Olmedo M.
  • Madsen A.

International Journal of Approximate Reasoning - 1/3/2016

10.1016/j.ijar.2015.11.011

Cite count: 2 (Web of Science) 2 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 2.845 (2016)
  • CiteScore: 7.1 (2020)
  • SJR: 1.275 (2016
  • SNIP: 1.852 (2016
  • JCR 5-year Impact Factor: 2.948
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Applied Mathematics (Q1); Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1)
Open Access

Evaluating interval-valued influence diagrams

  • Cabañas R.
  • Antonucci A.
  • Cano A.
  • Gómez-Olmedo M.

International Journal of Approximate Reasoning - 1/1/2017

10.1016/j.ijar.2016.05.004

Cite count: 7 (Web of Science) 9 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.766 (2017)
  • CiteScore: 7.1 (2020)
  • SJR: 0.866 (2017
  • SNIP: 1.746 (2017
  • JCR 5-year Impact Factor: 2.504
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1); Applied Mathematics (Q2)
Open Access

Efficient computation of counterfactual bounds

  • Zaffalon M.
  • Antonucci A.
  • Cabañas R.
  • Huber D.
  • Azzimonti D.

International Journal of Approximate Reasoning - 1/8/2024

10.1016/j.ijar.2023.109111

Cite count: 1 (Scopus)
  • CiteScore: 6.9 (2023)
  • SJR: 0.877 (2023
  • SNIP: 1.5 (2023
Open Access

Probabilistic Models with Deep Neural Networks

  • Andrés R. Masegosa
  • Rafael Cabañas De Paz
  • Helge Langseth
  • Thomas Dyhre Nielsen
  • Antonio Salmerón Cerdán

Entropy - 1/01/2021

10.3390/e23010117

Cite count: 4 (Web of Science)
  • JCR Quartile: Q2 (2021)
  • JCR Impact Factor: 2.738 (2023)
  • Category normalized Impact: 0.1 (2021)
  • CiteScore: 4 (2020)
  • SJR: 0.468 (2020
  • SNIP: 1.059 (2020
  • JCR 5-year Impact Factor: 2.642
  • JCR Categories: PHYSICS, MULTIDISCIPLINARY
Open Access

Learning Styles Impact Students’ Perceptions on Active Learning Methodologies: A Case Study on the Use of Live Coding and Short Programming Exercises

  • Andrés R. Masegosa
  • Rafael Cabañas
  • Ana D. Maldonado
  • María Morales

Education Sciences - 1/3/2024

10.3390/educsci14030250

Cite count: 1 (Scopus)
Open Access

Evaluating asymmetric decision problems with binary constraint trees

  • Cabañas R.
  • Gómez-Olmedo M.
  • Cano A.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 1/8/2013

10.1007/978-3-642-39091-3-8

Cite count:
  • CiteScore: 1.8 (2020)
  • SJR: 0.36 (2013
  • SNIP: 0.775 (2013
Open Access

On SPI-Lazy evaluation of influence diagrams

  • Cabañas R.
  • Cano A.
  • Gómez-Olmedo M.
  • Madsen A.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 1/1/2014

10.1007/978-3-319-11433-0_7

Cite count: 3 (Web of Science) 3 (Scopus)
  • CiteScore: 1.8 (2020)
  • SJR: 0.354 (2014
  • SNIP: 0.753 (2014
Open Access

Approximate lazy evaluation of influence diagrams

  • Cabañas R.
  • Cano A.
  • Gómez-Olmedo M.
  • Madsen A.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 10/10/2013

10.1007/978-3-642-40643-0_33

Cite count: 1 (Web of Science) 1 (Scopus)
  • CiteScore: 1.8 (2020)
  • SJR: 0.36 (2013
  • SNIP: 0.775 (2013
Open Access

Variable elimination for interval-valued influence diagrams

  • Cabañas R.
  • Antonucci A.
  • Cano A.
  • Gómez-Olmedo M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 1/1/2015

10.1007/978-3-319-20807-7_49

Cite count: 1 (Web of Science) 1 (Scopus)
  • CiteScore: 1.8 (2020)
  • SJR: 0.369 (2015
  • SNIP: 0.708 (2015

Heuristics for determining the elimination ordering in the influence diagram evaluation with binary trees

  • Cabañas R.
  • Cano A.
  • Gómez-Olmedo M.
  • Madsen A.

Frontiers in Artificial Intelligence and Applications - 1/12/2013

10.3233/978-1-61499-330-8-65

Cite count: 2 (Web of Science) 1 (Scopus)
  • SJR Quartile: Q3
  • CiteScore: 0.6 (2020)
  • SJR: 0.275 (2013
  • SNIP: 0.521 (2013
  • SJR Categories: Artificial Intelligence (Q3)

On SPI for Evaluating Influence Diagrams

  • Cabañas R.
  • Madsen A.
  • Cano A.
  • Gómez-Olmedo M.

Communications in Computer and Information Science - 1/1/2014

10.1007/978-3-319-08795-5_52

Cite count: 3 (Web of Science) 3 (Scopus)
  • SJR Quartile: Q4
  • CiteScore: 0.8 (2020)
  • SJR: 0.16 (2014
  • SNIP: 0.273 (2014
  • SJR Categories: Computer Science (miscellaneous) (Q4); Mathematics (miscellaneous) (Q4)

Virtual subconcept drift detection in discrete data using probabilistic graphical models

  • Cabañas R.
  • Cano A.
  • Gómez-Olmedo M.
  • Masegosa A.
  • Moral S.

Communications in Computer and Information Science - 1/1/2018

10.1007/978-3-319-91479-4_51

Cite count: 3 (Web of Science) 2 (Scopus)
  • SJR Quartile: Q3
  • Category normalized Impact: 0.39 (2018)
  • CiteScore: 0.8 (2020)
  • SJR: 0.168 (2018
  • SNIP: 0.397 (2018
  • SJR Categories: Computer Science (miscellaneous) (Q3); Mathematics (miscellaneous) (Q4)

Dynamic Bayesian networks for gesture recognition

XII Workshop de Agentes Físicos - WAF 2011, Albacete, 5 y 6 de septiembre de 2011, Proceedings - 2011

  • ORCID

Approximate inference in influence diagrams using binary trees

  • De Paz R.
  • Gómez-Olmedo M.
  • Cano A.

Proceedings of the 6th European Workshop on Probabilistic Graphical Models, PGM 2012 - 1/12/2012

Cite count: 6 (Scopus)
  • SJR Categories: Statistics and Probability

Financial Data Analysis with PGMs Using AMIDST

  • Cabanas R.
  • Martinez A.
  • Masegosa A.
  • Ramos-Lopez D.
  • Sameron A.
  • Nielsen T.
  • Langseth H.
  • Madsen A.
... View more Collapse

IEEE International Conference on Data Mining Workshops, ICDMW - 30/01/2017

10.1109/icdmw.2016.0185

Cite count: 4 (Web of Science) 4 (Scopus)
  • Category normalized Impact: 0.586 (2017)
  • SJR Categories: Computer Science Applications; Software

A Linear Programming Based Approach for Evaluating Interval-valued Influence Diagrams

  • Manuel Gómez Olmedo
  • Alessandro Antonucci
  • Rafael Cabañas de Paz
  • Andrés Cano Utrera

18th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2018, Granada, Spain, October 23-26, 2015, Proceedings - 2018

  • ORCID

This author has no patents.

This author has no reports or other types of publications.

Scopus: 4

Web of Science: 4

Scopus: 0

Web of Science: 0

Last data update: 11/2/24 7:51 AM
Next scheduled update: 11/9/24 3:00 AM