Time Series Forecasting with Gaussian Processes Needs Priors

  title={Time Series Forecasting with Gaussian Processes Needs Priors},
  author={Giorgio Corani and Alessio Benavoli and Marco Zaffalon},
. Automatic forecasting is the task of receiving a time series and returning a forecast for the next time steps without any human in-tervention. Gaussian Processes (GPs) are a powerful tool for modeling time series, but so far there are no competitive approaches for automatic forecasting based on GPs. We propose practical solutions to two problems: automatic selection of the optimal kernel and reliable estimation of the hyperparameters. We propose a fixed composition of kernels, which contains… 

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