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Number of items: 8.

Article

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.

Shen, Yuan; Cornford, Dan; Opper, Manfred and Archambeau, Cédric Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions. Computational Statistics, 27 (1), pp. 149-176.

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

Book Section

Shen, Yuan; Cornford, Dan and Opper, Manfred (2009). A basis function approach to Bayesian inference in diffusion processes. IN: IEEE/SP 15th Workshop on Statistical Signal Processing, 2009. SSP '09. IEEE.

Archambeau, Cédric; Opper, Manfred; Shen, Yuan; Cornford, Dan and Shawe-Taylor, John (2008). Variational inference for diffusion processes. IN: Annual Conference on Neural Information Processing Systems 2007. Platt, J.C.; Koller, D.; Singer, Y. and Roweis, S. (eds) Advances In Neural Information Processing Systems . Cambridge, MA (US): MIT.

Monograph

Olbrich, E.; Shen, Yuan; Fukao, K.; Meier, P.F. and Wieser, H.G. Nonlinearity in all-night sleep EEG recorded with foramen ovale electrodes in a patient with temporal lobe epilepsy. Technical Report. Aston University, Birmingham. (Unpublished)

Shen, Y.; Cornford, D.; Opper, M. and Archambeau, C. Variational Markov Chain Monte Carlo for Bayesian smoothing of non-linear niffusions. Technical Report. Aston University, Birmingham (UK). (Unpublished)

Vrettas, Michail D.; Shen, Yuan and Cornford, Dan Derivations of variational gaussian process approximation framework. Technical Report. Aston University, Birmingham.

This list was generated on Thu Jun 8 00:51:54 2017 BST.