Pérez Bernabé, Inmaculada Author
Parameter learning in hybrid Bayesian networks using prior knowledge
- Pérez-Bernabé I.
- Fernández A.
- Rumí R.
- Salmerón A.
Data Mining and Knowledge Discovery - 1/5/2016
- JCR Quartile: Q1 (2016)
- SJR Quartile: Q1
- JCR Impact Factor: 3.16 (2022)
- Category normalized Impact: 0.144 (2016)
- CiteScore: 8.3 (2020)
- SJR: 1.14 (2016
- SNIP: 2.341 (2016
- JCR 5-year Impact Factor: 3.477
- JCR Categories: COMPUTER SCIENCE, INFORMATION SYSTEMS
- SJR Categories: Computer Networks and Communications (Q1); Computer Science Applications (Q1); Information Systems (Q1)
- Scopus
- ORCID
- Web of Science
MoTBFs: An R Package for Learning Hybrid Bayesian Networks Using Mixtures of Truncated Basis Functions
- Pérez-Bernabé I.
- Maldonado A.D.
- Nielsen T.D.
- Salmerón A.
The R Journal - 1/1/2020
- JCR Impact Factor: 3.984 (2020)
- JCR 5-year Impact Factor: 7.958
- JCR Categories: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
On using the PC algorithm for learning continuous Bayesian networks: An experimental analysis
- Fernández A.
- Pérez-Bernabé I.
- Salmerón A.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 10/10/2013
- Category normalized Impact: 0.273 (2013)
- CiteScore: 1.8 (2020)
- SJR: 0.36 (2013
- SNIP: 0.775 (2013
- Scopus
- ORCID
- Web of Science
Incorporating prior knowledge when learning mixtures of truncated basis functions from data
- Fernández A.
- Pérez-Bernabé I.
- Rumí R.
- Salmerón A.
Twelfth Scandinavian Conference on Artificial Intelligence (Scai 2013) - 1/12/2013
- SJR Quartile: Q3
- Category normalized Impact: 0.136 (2013)
- CiteScore: 0.6 (2020)
- SJR: 0.275 (2013
- SNIP: 0.521 (2013
- SJR Categories: Artificial Intelligence (Q3)
- Scopus
- ORCID
- Web of Science
Learning hybrid bayesian networks using mixtures of truncated basis functions. Aprendizaje de redes bayesianas híbridas con mixturas de funciones base truncadas
- Inmaculada Pérez-Bernabé
- Antonio Salmerón Cerdán
- Helge Langseth
2015
- Dialnet
Learning mixtures of truncated basis functions from data
- Langseth H.
- Nielsen T.
- Pérez-Bernabé I.
- Salmerón A.
International Journal of Approximate Reasoning - 1/1/2012
- JCR Quartile: Q1 (2012)
- SJR Quartile: Q1
- JCR Impact Factor: 2.451 (2022)
- Category normalized Impact: 0.81 (2012)
- CiteScore: 7.1 (2020)
- SJR: 1.46 (2014
- SNIP: 2.845 (2014
- JCR 5-year Impact Factor: 2.51
- JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
- SJR Categories: Applied Mathematics (Q1); Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1)
- Scopus
- Scopus
- ORCID
- OAI-PMH
- Web of Science
Learning conditional distributions using mixtures of truncated basis functions
- Pérez-Bernabé I.
- Salmerón A.
- Langseth H.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 1/1/2015
- Category normalized Impact: 0.293 (2015)
- CiteScore: 1.8 (2020)
- SJR: 0.369 (2015
- SNIP: 0.708 (2015
This author has no patents.
This author has no reports or other types of publications.
h index
Scopus: 2
Web of Science: 2
i10 index
Scopus: 0
Web of Science: 1
Research groups
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Análisis de datos
Role: Miembro
Author profiles
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Scopus Author ID
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Dialnet id
Research projects at UAL
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Acronym P12-TIC-2541Since: January 30, 2014Until: January 29, 2016Funded by: JUNTAFunding / grant amount: 7,920.00 EURRole: Investigador
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Acronym P11-TIC-07821Since: April 30, 2013Until: April 30, 2015Funded by: JUNTAFunding / grant amount: 19,665.00 EURRole: Investigador