- Abstract:
-
Variational Bayes (VB) has been proposed as a method to facilitate calculations of the posterior distributions for linear models, by providing a fast method for Bayesian inference by estimating the parameters of a factorized approximation to the posterior distribution. Here a VB method for nonlinear forward models with Gaussian additive noise is presented. In the case of noninformative priors the parameter estimates obtained from this VB approach are identical to those found via nonlinear lea...
Expand abstract - Publication status:
- Published
- Publisher copy:
- 10.1109/TSP.2008.2005752
-
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- Journal:
- IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Volume:
- 57
- Issue:
- 1
- Pages:
- 223-236
- Publication date:
- 2009-01-05
- DOI:
- EISSN:
-
1941-0476
- ISSN:
-
1053-587X
- URN:
-
uuid:1e31142d-b892-4910-807f-7cf44f290a9b
- Source identifiers:
-
186271
- Local pid:
- pubs:186271
- Language:
- English
- Keywords:
- Copyright date:
- 2009
Journal article
Variational Bayesian Inference for a Nonlinear Forward Model
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