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PhD Thesis

Efficient Reinforcement Learning using Gaussian Processes

Marc Peter Deisenroth

Combining Genetic Algorithms and Neural Networks: The Encoding Problem

 Philipp Koehn

EVALUATION OF GAUSSIAN PROCESSES AND OTHER METHODS FOR NON-LINEAR REGRESSION

Carl Edward Rasmussen

Multi-fidelity Gaussian process regression for computer experiments

Loic Le Gratiet

Design and Analysis of Computer Experiments for Screening Input Variables

Hyejung Moon

Global sensitivity analysis for nested and multiscale modelling

Yann Caniou

UNCERTAINTY ANALYSIS FOR COMPUTER SIMULATIONS THROUGH VALIDATION AND CALIBRATION

John Milburn McFarland

UNCERTAINTY QUANTIFICATION IN TIME-DEPENDENT RELIABILITY ANALYSIS

You Ling

Deep Learning for Reinforcement Learning in Pacman

Bachelor-Thesis von Aaron Hochländer aus Wiesbaden

Gaussian Processes – Iterative Sparse Approximations

Lehel Csato

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