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Gaussian Process : PhD Thesis

Efficient Reinforcement Learning using Gaussian Processes

Marc Peter Deisenroth

Gaussian Processes for Regression and Optimisation

Phillip Boyle

Covariance Kernels for Fast Automatic Pattern Discovery and Extrapolation with Gaussian Processes

Andrew Gordon Wilson

Deep Gaussian Processes and Variational Propagation of Uncertainty

Andreas Damianou

Gaussian Process Models for Robust Regression, Classification, and Reinforcement Learning

M. Kuss

Approximate Methods for Propagation of Uncertainty with Gaussian Process Models

Agathe Girard

GAUSSIAN PROCESS REGRESSION TECHNIQUES WITH APPLICATIONS TO WIND TURBINES

HILDO BIJL Gaussian Process Regression Techniques – The source code corresponding to the Ph.D. thesis

Learning from Demonstration with Gaussian Processes

Markus Schneider

Nonlinear Modelling and Control using Gaussian Processes

Andrew McHutchon

NONSTATIONARY GAUSSIAN PROCESSES FOR REGRESSION AND SPATIAL MODELLING

Christopher Joseph Paciorek

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