Pérez Bernabé, Inmaculada Autor

Open Access

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

10.32614/rj-2021-019

Número de citas:

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

10.1007/s10618-015-0429-7

Número de citas: 3 (Web of Science) 4 (Scopus)
Open Access

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

10.1007/978-3-319-20807-7_36

Número de citas: 2 (Web of Science) 2 (Scopus)

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

Número de citas:
  • Dialnet

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

10.3233/978-1-61499-330-8-95

Número de citas: 1 (Web of Science) 2 (Scopus)
Open Access

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

10.1007/978-3-642-40643-0_35

Número de citas: 2 (Web of Science) 2 (Scopus)
Open Access

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

10.1016/j.ijar.2013.09.012

Número de citas: 23 (Web of Science) 9 (Scopus)

Este autor no tiene patentes.

Este autor no tiene informes ni otros tipos de publicaciones.

Scopus: 2

Web of Science: 2

Scopus: 0

Web of Science: 1

Última actualización de los datos: 12/10/24 11:59
Próxima recolección programada: 19/10/24 3:00