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Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models
In this paper, we describe a general variational Bayesian approach for approximate inference on nonlinear stochastic dynamic models. This scheme extends established approximate inference on hidden-states to cover: (i) nonlinear evolution and observation functions, (ii) unknown parameters and (precis...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
North-Holland
2009
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2767160/ https://www.ncbi.nlm.nih.gov/pubmed/19862351 http://dx.doi.org/10.1016/j.physd.2009.08.002 |