Blog – Page 12 – machine-learning-2020

Gaussian Process : Papers

A Metamodeling Method Using Dynamic Kriging and Sequential Sampling Scalable Gaussian Process Regression Using Deep Neural Networks VARIATIONAL AUTO-ENCODED DEEP GAUSSIAN PROCESSES Deep Kernel Learning Training Deep Gaussian Processes using Stochastic Expectation Propagation and Probabilistic Backpropagation Deep Gaussian Processes for Regression using Approximate Expectation Propagation Warped Gaussian Processes Occupancy Mapping with Uncertain Inputs Introduction to … Read more

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

Web sites

Neural Networks – A Systematic Introduction – book online Neural Networks and Deep Learning : free online book Probabilistic Programming & Bayesian neural networks research group DART-Europe E-theses Portal Kernel-Machines.Org The Gaussian Processes Web Site SIAM : Society for Industrial and Applied Mathematics Arxiv Sanity Preserver scikit-learn – Gaussian Process Open archive HAL – HAL … Read more