A variational radial basis function approximation for diffusion processes

ESANN 2009 Proceedings, 17th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning

Volumn , Issue , 2009, Pages 497-502

  Vrettas, Michail D ^a   Cornford, Dan ^a   Shen, Yuan ^a  

^a ASTON UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATE INFERENCE; DIFFUSION PROCESS; DOUBLE-WELL POTENTIAL; NEW APPROACHES; ORIGINAL ALGORITHMS; RADIAL BASIS FUNCTIONS; VARIATIONAL ALGORITHMS;

DIFFUSION; DYNAMICAL SYSTEMS; INFERENCE ENGINES; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS;

APPROXIMATION ALGORITHMS;

EID: 79957514371     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Peter E. Kloeden and Eckhard Platen. Numerical Solutions of Stochastic Differential Equations, Springer-Verlag, Berlin, 1992.
2. Christopher M. Bishop. Neural Networks for Pattern Recognition, Oxford University Press, New York, 1995.
3. D. S. Broomhead and D. Lowe. Multivariate functional interpolation and adaptive networks. Complex Systems, 2:321-355, 1988.
4. S. Kullback and R. A. Leibler, On information and sufficiency. Annal of Mathematical Statistics, 22:79-86, 1951.
5. A. Golightly and D. J. Wilkinson. Bayesian inference for non-linear multivariate diffusion models observed with error. Computational Statistics and Data Analysis, 2007. Accepted.
6. C. Archambeau, D. Cornford, M. Opper and J. Shawe Taylor. Gaussian process approximation of stochastic differential equations. Journal of Machine Learning Research, Workshop and Conference Proceedings, 1:1-16, 2007.
7. V. K °urkova and K. Hlavačkova. Approximation of Continuous Functions by RBF and KBF Networks. ESANN, Proceedings, pp. 167-74, 1994.
8. T. Jaakkola. Tutorial on variational approximation methods. In M. Opper and D. Saad, editors, Advanced Mean Field Methods: Theory and Practise, The MIT press, 2001.
9. C. Archambeau, M. Opper, Y. Shen, D. Cornford, J. Shawe-Taylor. Variational Inference for Diffusion Processes. In C. Platt, D. Koller, Y. Singer and S. Roweis editors, Neural Information Processing Systems (NIPS) 20, pages 17-24, 2008. The MIT Press.
10. M. D. Vrettas, Y. Shen and D. Cornford. Derivations of Variational Gaussian Process Approximation. Technical Report (NCRG/2008/002). Neural Computing Research Group, Aston University, Birmingham, B4 7ET, United Kingdom, March 2008.