A new variational radial basis function approximation for inference in multivariate diffusions


Autoria(s): Vrettas, Michail D.; Cornford, Dan; Opper, Manfred; Shen, Yuan
Data(s)

01/03/2010

Resumo

In this paper we present a radial basis function based extension to a recently proposed variational algorithm for approximate inference for diffusion processes. Inference, for state and in particular (hyper-) parameters, in diffusion processes is a challenging and crucial task. We show that the new radial basis function approximation based algorithm converges to the original algorithm and has beneficial characteristics when estimating (hyper-)parameters. We validate our new approach on a nonlinear double well potential dynamical system.

Formato

application/pdf

Identificador

http://eprints.aston.ac.uk/16242/1/Vrettas2009ESANN.pdf

Vrettas, Michail D.; Cornford, Dan; Opper, Manfred and Shen, Yuan (2010). A new variational radial basis function approximation for inference in multivariate diffusions. Neurocomputing, 73 (7-9), pp. 1186-1198.

Relação

http://eprints.aston.ac.uk/16242/

Tipo

Article

PeerReviewed