Regression with Input-dependent Noise , in M. I. Jordan, M. J. Kearns and S. A. Solla, eds. Lecture notes for a tutorial at NIPS 1997. Monte Carlo implementation of Gaussian process models for Bayesian regression and classification , technical report no. 9702, Department of Statistics, University of Toronto. On curve fitting and optimal design for regression , Journal of the Royal Statistical Society B, vol. Bayesian Regression using Gaussian Process priors , presentation at the meeting of the American Statistical Association in Chicago, Aug. 4-8.
Slides are available in postscript .
Evaluation of Gaussian Processes and other Methods for Non-Linear Regression , PhD thesis, graduate department of Computer Science, University of Toronto. Learning curves for Gaussian processes , to appear in Advances in Neural Information Processing Systems 11, M. J. Kearns, S. A. Solla, and D. Cohn, editors, MIT Press, Cambridge, MA. abstract , postscript . Improper priors, spline smoothing and the problem of guarding against model errors in regression , Journal of the Royal Statistical Society B, vol. Sline Models for Observational Data , vol. S. W. Ellacott, J. C. Mason and I. J. Anderson, Kluwer, 1997.