Machine Learning Techniques
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
Gaussian Process : Deep Gaussian Process – Warped Gaussian Process -Additive Kernel
The Deep Feed-Forward Gaussian Process: An Effective Generalization to Covariance Priors Warped Gaussian Processes Occupancy Mapping with Uncertain Inputs Warped Gaussian Processes Manifold Gaussian Processes for Regression Sparse Gaussian Processes using Pseudo-inputs Deep Gaussian Processes Chained Gaussian Processes Student-t Processes as Alternatives to Gaussian Processe Introduction to Gaussian Process Additive Gaussian Processes ACCURACY VERSUS INTERPRETABILITY … 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