Priors for Bayesian Neural Networks
In recent years, Neural Networks (NN) have become a popular data-analytic tool in Statistics, Computer Science and many other fields. NNs can be used as universal approximators, that is, a tool for regressing a dependent variable on a possibly complicated function of the explanatory variables. Th...
Main Author: | Robinson, Mark |
---|---|
Language: | English |
Published: |
2009
|
Online Access: | http://hdl.handle.net/2429/11911 |
Similar Items
-
Priors for Bayesian Neural Networks
by: Robinson, Mark
Published: (2009) -
Physics-Prior Bayesian Neural Networks in Semiconductor Processing
by: Chun Han Chen, et al.
Published: (2019-01-01) -
Iterative Aggregation of Bayesian Networks Incorporating Prior Knowledge
by: Xu, Jian
Published: (2004) -
Weyl Prior and Bayesian Statistics
by: Ruichao Jiang, et al.
Published: (2020-04-01) -
Paradoxes and Priors in Bayesian Regression
by: Som, Agniva
Published: (2014)