Gaussian Process : PhD Thesis
UNCERTAINTY ANALYSIS FOR COMPUTER SIMULATIONS THROUGH VALIDATION AND CALIBRATION
John Milburn McFarland
Deep Learning for Reinforcement Learning in Pacman
Bachelor-Thesis von Aaron Hochländer aus Wiesbaden
Efficient Reinforcement Learning using Gaussian Processes
Marc Peter Deisenroth
Learning with Uncertainty – Gaussian Processes and Relevance Vector Machines
Joaquin Quinonero Candela
Probabilistic Feature Learning Using Gaussian Process Auto-Encoders
Simon Olofson – PhD Thesis Reference from PhD Thesis: Auto-Encoding Variational Bayes Stochastic Backpropagation and Approximate Inference in Deep Generative Models Generalized Product of Experts for Automatic and Principled Fusion of Gaussian Process Predictions From Pixels to Torques: Policy Learning with Deep Dynamical Models Sparse Greedy Gaussian Process Regression Autoencoders, Unsupervised Learning, and Deep … Read more
SIMULATION METAMODELING AND OPTIMIZATION WITH AN ADDITIVE GLOBAL AND LOCAL GAUSSIAN PROCESS MODEL FOR STOCHASTIC SYSTEMS
MENG QUN AN ADDITIVE GLOBAL AND LOCAL GAUSSIAN PROCESS MODEL FOR LARGE DATA SETS