Online Regression for Data With Changepoints Using Gaussian Processes and Reusable Models.

Many prediction, decision-making, and control architectures rely on online learned Gaussian process (GP) models. However, most existing GP regression algorithms assume a single generative model, leading to poor predictive performance when the data are nonstationary, i.e.