Learning – Page 7 – machine-learning-2020

NONLINEAR DYNAMICS IDENTIFICATION USING GAUSSIAN PROCESS PRIOR MODELS WITHIN A BAYESIAN CONTEXT

Keith Neo Kian Seng

Bayesian Gaussian Processes for Regression and Classification

Mark N. Gibbs

Keyon Vafa

Training and Inference for Deep Gaussian Processes

Nicolas Durrande’s homepage (kernel based methods for interpolation or approximation problems, both from the Gaussian process and RKHS point of view) Phd Thesis (in French) Phd Thesis (slides in English)

Étude de classes de noyaux adaptées à la simplification et à l’interprétation des modèles d’approximation. Une approche fonctionnelle et probabiliste

Nicolas Durrande

Neil Lawrence

Machine Learning Index of /home/neil/

Amund Tveit

Deep Learning with Gaussian Process

Andreas Damianou

personal homepage Publications

Efficient Reinforcement Learning using Gaussian Processes

Marc Peter Deisenroth

Combining Genetic Algorithms and Neural Networks: The Encoding Problem

Philipp Koehn