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Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood
Gaussian process multiclass classification multinomial probit approximate inference expectation propagation
2012/9/19
We consider probabilistic multinomial probit classification using Gaussian process (GP) priors. The challenges with the multiclass GP classification are the integration over the non-Gaussian posterior...
Expectation Propagation in Gaussian Process Dynamical Systems
Expectation Propagation Gaussian Process Dynamical Systems
2012/9/19
Rich and complex time-series data, such as those generated from engineer-ing systems, financial markets, videos or neural recordings, are now a common feature of modern data analysis. Explaining the p...
Bayesian inference with rescaled Gaussian process priors
Rate of convergence Bayesian inference nonparametric density estimation nonparametric regression classification
2009/9/16
We use rescaled Gaussian processes as prior models for functional parameters in nonparametric statistical models. We show how the rate of contraction of the posterior distributions depends on the scal...
Lower bounds for posterior rates with Gaussian process priors
Bayesian nonparametrics Gaussian process priors Lower bounds
2009/9/16
Upper bounds for rates of convergence of posterior distributions associated to Gaussian process priors are obtained by van der Vaart and van Zanten in [van der Vaart and van Zanten, Rates of contracti...