Rasmussen, C. E. and Ghahramani, Z.
Bayesian Monte Carlo abstract ps pdf.
Draft accepted by NIPS*02.
Solak, E., Murray-Smith, R., Leithead, W. E., Leith, D. J. and Rasmussen C. E.
Derivative observations in Gaussian Process models of dynamic systems abstract ps
Draft accepted by NIPS*02.
Girard, A. C., Rasmussen, C. E. and Murray-Smith, R.
Multiple-step ahead prediction for non linear dynamic systems -- A Gaussian Process treatment with propagation of the uncertainty abstract ps
Draft accepted by NIPS*02.
Rasmussen, C. E.
Gaussian Processes to Speed up Hybrid Monte Carlo for Expensive Bayesian Integrals abstract ps.
Draft submitted to Bayesian Statistics 7.
Andersen, I. K., Szymkowiak A., Rasmussen, C. E., Hanson L. G., Marstrand J. R., Larsson H. B. W. and Hansen L. K.
Perfusion Quantification using Gaussian Process Deconvolution abstract, ps, pdf.
Magnetic Resonance in Medicine, 48:351-361, Wiley (2002).
Rasmussen, C. E. and Ghahramani, Z.
Infinite Mixtures of Gaussian Process Experts abstract ps pdf.
Advances in Neural Information Processing Systems 14, eds. T. Dietterich, S. Becker, Z. Ghahramani, MIT Press (2002).
Beal, M. J., Ghahramani, Z. and Rasmussen, C. E.
The Infinite Hidden Markov Model abstract ps pdf.
Advances in Neural Information Processing Systems 14, eds. T. Dietterich, S. Becker, Z. Ghahramani, MIT Press (2002).
Rasmussen, C. E and Ghahramani, Z. (2000)
Occam's Razor abstract ps pdf.
Advances in Neural Information Processing Systems 13, eds. T. Leen, T. Dietterich, V. Tresp, MIT Press (2001).
Rasmussen, C. E. (1999)
The Infinite Gaussian Mixture Model abstract ps pdf.
Advances in Neural Information Processing Systems 12, S.A. Solla,
T.K. Leen and K.-R. Müller (eds.), pp. 554-560, MIT Press (2000).
Højen-Sørensen, P. A. d. F. R., Hansen, L. K. and Rasmussen, C. E. (1999)
Bayesian modelling of fMRI time series abstract ps pdf.
Advances in Neural Information Processing Systems 12, S.A. Solla,
T.K. Leen and K.-R. Müller (eds.), pp. 754-760, MIT Press (2000).
Rasmussen, C. E. (1996)
Evaluation of Gaussian Processes and other Methods for Non-Linear Regression abstract ps.
Ph.D. thesis, Graduate Department of Computer Science, University of Toronto.
Rasmussen, C. E. (1996)
A Practical Monte Carlo Implementation of Bayesian Learning abstract ps.
Advances in Neural Information Processing Systems 8, eds. D. S. Touretzky, M. C. Mozer, M. E. Hasselmo, MIT Press, 1996, pp. 598-604.
Williams, C. K. I. and Rasmussen, C. E. (1996)
Gaussian Processes for Regression abstract ps.
Advances in Neural Information Processing Systems 8, eds. D. S. Touretzky, M. C. Mozer, M. E. Hasselmo, MIT Press, 1996, pp. 514-520.
Lars K. Hansen, Carl E. Rasmussen, Claus Svarer & Jan Larsen " Adaptive Regularization", Proceedings of the 1994 IEEE-NNSP workshop, Greece, September 1994.
Lars K. Hansen & Carl E. Rasmussen " Pruning from Adaptive Regularization", Neural Computation, vol 6:6, pp 1222-1231, (1994).
Claus Svarer, Lars K. Hansen, Jan Larsen & Carl E. Rasmussen " Designer Networks for time series processing", Proceedings of the III IEEE Workshop on Neural Networks for Signal Processing, eds. C. A. Kamm, G. M. Kuhn, B. Yoon, R. Chellappa & S. Y. Kung, IEEE Press, 1993, pp. 78-87.
Rasmussen, C. E. and Willshaw, D. J. (1993)
Presynaptic and Postsynaptic Competition in models for the Development of Neuromuscular Connections abstract ps.
Biological Cybernetics, vol 68, pp 409-419, (1993).
Invited talk at the Bayesian modelling Conference at the Newton Institute, Cambrige, England, December 14-19, 1997 entitled "Bayesian Regression using Gaussian Process priors".
Invited talk at the meeting of the American Statistical Association in Chicago, Aug. 4-8, 1996 entitled "Bayesian Regression using Gaussian Process priors".