Proceedings of Machine Learning Research

Volume 1: Gaussian Processes in Practice, 12-13 June 2006, Bletchley Park, UK

Editors: Neil D. Lawrence, Anton Schwaighofer, Joaquin Quiñonero Candela

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Gaussian Process Approximations of Stochastic Differential Equations

Cedric Archambeau, Dan Cornford, Manfred Opper, John Shawe-Taylor; Gaussian Processes in Practice, PMLR 1:1-16

Multi-class Semi-supervised Learning with the $\epsilon$-truncated Multinomial Probit Gaussian Process

Simon Rogers, Mark Girolami; Gaussian Processes in Practice, PMLR 1:17-32

Learning RoboCup-Keepaway with Kernels

Tobias Jung, Daniel Polani; Gaussian Processes in Practice, PMLR 1:33-57

Salient Point and Scale Detection by Minimum Likelihood

Kim S. Pedersen, Marco Loog, Pieter Dorst; Gaussian Processes in Practice, PMLR 1:59-72

Sparse Log Gaussian Processes via MCMC for Spatial Epidemiology

Jarno Vanhatalo, Aki Vehtari; Gaussian Processes in Practice, PMLR 1:73-89