Shen, Yuan, Archambeau, Cédric, Cornford, Dan, Opper, Manfred, Shawe-Taylor, John and Barillec, Remi (2010). A comparison of variational and Markov chain Monte Carlo methods for inference in partially observed stochastic dynamic systems. Journal of Signal Processing Systems, 61 (1), pp. 51-59.
Abstract
In recent work we have developed a novel variational inference method for partially observed systems governed by stochastic differential equations. In this paper we provide a comparison of the Variational Gaussian Process Smoother with an exact solution computed using a Hybrid Monte Carlo approach to path sampling, applied to a stochastic double well potential model. It is demonstrated that the variational smoother provides us a very accurate estimate of mean path while conditional variance is slightly underestimated. We conclude with some remarks as to the advantages and disadvantages of the variational smoother. © 2008 Springer Science + Business Media LLC.
| Publication DOI: | https://doi.org/10.1007/s11265-008-0299-y |
|---|---|
| Divisions: | ?? 50811700Jl ?? College of Engineering & Physical Sciences > Systems analytics research institute (SARI) |
| Additional Information: | The original publication is available at www.springerlink.com |
| Uncontrolled Keywords: | Bayesian computation,data assimilation,nonlinear smoothing,signal processing,variational approximation,Hardware and Architecture,Information Systems,Signal Processing,Theoretical Computer Science,Control and Systems Engineering,Modelling and Simulation |
| Publication ISSN: | 1939-8115 |
| Last Modified: | 06 Oct 2025 07:06 |
| Date Deposited: | 11 Mar 2019 17:43 |
| Full Text Link: |
http://www.spri ... 57174m00231v04/ |
| Related URLs: |
http://www.scop ... tnerID=8YFLogxK
(Scopus URL) |
PURE Output Type: | Article |
| Published Date: | 2010-10 |
| Published Online Date: | 2008-11-11 |
| Authors: |
Shen, Yuan
Archambeau, Cédric Cornford, Dan ( 
0000-0001-8787-6758)
Opper, Manfred Shawe-Taylor, John Barillec, Remi |