Gaussian Process Regression Explained. Aug 09 2016 Gaussian Processes GPs are the natural next step in that journey as they provide an alternative approach to regression problems. Lets start with a distribution of all possible functions that conceivably could have generated our data without actually looking at the data.
All of these instances are about regression. Training on inputs and outputs with the ultimate goal of prediction and uncertainty quantification UQ and ancillary goals that are either tantamount to or at least crucially depend upon qualities and quantities derived from a predictive distribution. In particular we will talk about a kernel-based fully Bayesian regression algorithm known as Gaussian process regression.
Jan 16 2019 Gaussian processes are a non-parametric method.
A Gaussian process can represent obliquely but rigorously by letting the data speak more clearly for themselves. Gaussian process GP is a very generic term. Rather than claiming relates to some specific models eg. ARMA models used in time series analysis and spline smoothing eg.
