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Cabañas de Paz, Rafael Author

Open Access

Bayesian networks for causal analysis in socioecological systems

  • Rafael Cabañas
  • Ana D. Maldonado
  • María Morales
  • Pedro A. Aguilera
  • Antonio Salmerón

Ecological Informatics - 1/11/2025

10.1016/j.ecoinf.2025.103173

Cite count: 0 (Scopus)
  • CiteScore: 11.4 (2024)
  • SJR: 1.491 (2024
  • SNIP: 1.795 (2024
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: 4 (Web of Science) 7 (Scopus)
Open Access

Probabilistic Models with Deep Neural Networks

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

ENTROPY - 1/1/2021

10.3390/e23010117

Cite count: 8 (Web of Science) 8 (Scopus)
  • JCR Quartile: Q2 (2021)
  • JCR Impact Factor: 2.738 (2023)
  • Category normalized Impact: 0.1 (2021)
  • CiteScore: 5.2 (2024)
  • SJR: 0.553 (2021
  • SNIP: 1.079 (2021
  • JCR 5-year Impact Factor: 2.642
  • JCR Categories: PHYSICS, MULTIDISCIPLINARY
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) 3 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 2.845 (2016)
  • CiteScore: 6.9 (2023)
  • SJR: 1.275 (2016
  • SNIP: 1.861 (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) 10 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.766 (2017)
  • CiteScore: 6.9 (2023)
  • SJR: 0.866 (2017
  • SNIP: 1.785 (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

Approximating counterfactual bounds while fusing observational, biased and randomised data sources

  • Zaffalon, Marco
  • Antonucci, Alessandro
  • Cabanas, Rafael
  • Huber, David

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING - 1/11/2023

10.1016/j.ijar.2023.109023

Cite count: 2 (Web of Science) 5 (Scopus)
  • JCR Quartile: Q2 (2023)
  • JCR Impact Factor: 3.2 (2023)
  • Category normalized Impact: 0.243 (2023)
  • CiteScore: 6.9 (2023)
  • SJR: 0.877 (2023
  • SNIP: 1.5 (2023
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 (Web of Science) 4 (Scopus)
  • CiteScore: 6.9 (2023)
  • SJR: 0.877 (2023
  • SNIP: 1.5 (2023
Open Access

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: 2 (Web of Science) 3 (Scopus)
  • JCR Quartile: Q2 (2021)
  • JCR Impact Factor: 8.993 (2022)
  • Category normalized Impact: 0.104 (2021)
  • CiteScore: 11.3 (2023)
  • SJR: 1.693 (2021
  • SNIP: 1.759 (2021
  • JCR 5-year Impact Factor: 8.926
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Using Binary Trees for the Evaluation of Influence Diagrams

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

INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS - 1/2/2016

10.1142/s0218488516500045

Cite count: 4 (Web of Science) 4 (Scopus)
  • SJR Quartile: Q2
  • JCR Impact Factor: 1.214 (2016)
  • CiteScore: 2.7 (2023)
  • SJR: 0.591 (2016
  • SNIP: 0.78 (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)
Open Access

InferPy: Probabilistic modeling with Tensorflow made easy

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

KNOWLEDGE-BASED SYSTEMS - 15/3/2019

10.1016/j.knosys.2018.12.030

Cite count: 7 (Web of Science) 7 (Scopus)
  • JCR Quartile: Q1 (2019)
  • SJR Quartile: Q1
  • JCR Impact Factor: 5.921 (2023)
  • Category normalized Impact: 0.298 (2019)
  • CiteScore: 15 (2024)
  • SJR: 1.754 (2019
  • SNIP: 2.789 (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)

This author has no books, chapters or theses.

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

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

2016 IEEE 16TH INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW) - 30/01/2016

10.1109/icdmw.2016.170

Cite count: 5 (Web of Science) 5 (Scopus)
  • Category normalized Impact: 0.586 (2016)
  • CiteScore: 1.6 (2024)
  • SJR: 0.178 (2016
  • SNIP: 0.431 (2016
  • SJR Categories: Computer Science Applications; Software
Open Access

Approximate Lazy Evaluation of Influence Diagrams

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

ADVANCES IN ARTIFICIAL INTELLIGENCE, CAEPIA 2013 - 10/10/2013

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

Cite count: 1 (Web of Science) 1 (Scopus)
  • CiteScore: 2.6 (2023)
  • SJR: 0.36 (2013
  • SNIP: 0.777 (2013
Open Access

On Counterfactual Explanations of Cardiovascular Risk in Adolescent and Young Adult Breast Cancer Survivors

  • Bernasconi A.
  • Balordi A.
  • Zanga A.
  • Cabañas R.

CEUR Workshop Proceedings - 1/1/2024

Cite count: 0 (Scopus)
  • CiteScore: 1.1 (2023)

Virtual Subconcept Drift Detection in Discrete Data Using Probabilistic Graphical Models

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

INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS: APPLICATIONS, IPMU 2018, PT III - 1/1/2018

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

Cite count: 3 (Web of Science) 3 (Scopus) 0 (Dialnet)
  • SJR Quartile: Q3
  • Category normalized Impact: 0.39 (2018)
  • CiteScore: 1.1 (2024)
  • SJR: 0.168 (2018
  • SNIP: 0.401 (2018
  • SJR Categories: Computer Science (miscellaneous) (Q3); Mathematics (miscellaneous) (Q4)

On SPI for Evaluating Influence Diagrams

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

INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, PT I - 1/1/2014

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

Cite count: 3 (Web of Science) 3 (Scopus)
  • SJR Quartile: Q4
  • CiteScore: 1.1 (2023)
  • SJR: 0.16 (2014
  • SNIP: 0.273 (2014
  • SJR Categories: Computer Science (miscellaneous) (Q4); Mathematics (miscellaneous) (Q4)

Diversity and Generalization in Neural Network Ensembles

  • Ortega, Luis A.
  • Cabanas, Rafael
  • Masegosa, Andres R.
  • Camps-Valls, G
  • Ruiz, FJR
  • Valera, I

INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 151 - 1/1/2022

Cite count: 16 (Web of Science) 30 (Scopus)
  • CiteScore: 8.9 (2024)
  • SNIP: 1.252 (2022
Open Access

A Divide and Conquer Approach for Solving Structural Causal Models

  • Bjøru, Anna Rodum
  • Cabañas De Paz, Rafael
  • Langseth, Helge
  • Salmerón Cerdán, Antonio

INTERNATIONAL CONFERENCE ON PROBABILISTIC GRAPHICAL MODELS - 1/1/2024

Cite count: 1 (Web of Science) 1 (Scopus)
  • CiteScore: 8.9 (2024)
  • SJR: 1.17 (2024
  • SNIP: 1.948 (2024

CREMA: A Java Library for Credal Network Inference

  • Huber, David
  • Cabanas, Rafael
  • Antonucci, Alessandro
  • Zaffalon, Marco
  • Jaeger, M
  • Nielsen, TD

INTERNATIONAL CONFERENCE ON PROBABILISTIC GRAPHICAL MODELS, VOL 138 - 1/1/2020

Cite count: 2 (Web of Science) 7 (Scopus)
  • SNIP: 1.033 (2020

Structural Causal Models Are (Solvable by) Credal Networks

  • Zaffalon, Marco
  • Antonucci, Alessandro
  • Cabanas, Rafael
  • Jaeger, M
  • Nielsen, TD

INTERNATIONAL CONFERENCE ON PROBABILISTIC GRAPHICAL MODELS, VOL 138 - 1/1/2020

Cite count: 10 (Web of Science) 14 (Scopus)
  • SNIP: 1.033 (2020

This author has no patents.

This author has no reports or other types of publications.

Scopus: 7

Web of Science: 6

Scopus: 4

Web of Science: 2

Last data update: 6/7/25 4:39 AM
Next scheduled update: 6/14/25 3:00 AM