Approximate Probability Propagation with Mixtures of Truncated Exponentials*
Mixtures of truncated exponentials (MTEs) are a powerful alternative to discretisation when working with hybrid Bayesian networks. One of the features of the MTE model is that standard propagation algorithms can be used. However, the complexity of the process is too high and therefore approximate me...
Main Authors: | Rumí, Rafael, Salmerón Cerdán, Antonio |
---|---|
格式: | info:eu-repo/semantics/article |
語言: | English |
出版: |
2017
|
主題: | |
在線閱讀: | http://hdl.handle.net/10835/4890 https://doi.org/10.1016/j.ijar.2006.06.007 |
相似書籍
-
Mixtures of Truncated Basis Functions
由: Langseth, Helge, et al.
出版: (2017) -
Learning hybrid Bayesian networks using mixtures of truncated exponentials
由: Romero, Vanessa, et al.
出版: (2017) -
Learning Mixtures of Truncated Basis Functions from Data
由: Langseth, Helge, et al.
出版: (2017) -
Dynamic Importance Sampling in Bayesian Networks Based on Probability Trees
由: Moral, Serafín, et al.
出版: (2017) -
Regression using hybrid Bayesian networks: modelling landscape - socioeconomy relationships
由: Fernández Ropero, Rosa María, et al.
出版: (2024)