Convergence of Gaussian Process Regression with Estimated Hyper-parameters and Applications in Bayesian Inverse Problems

17 Jul 2020 Teckentrup Aretha L

This work is concerned with the convergence of Gaussian process regression. A particular focus is on hierarchical Gaussian process regression, where hyper-parameters appearing in the mean and covariance structure of the Gaussian process emulator are a-priori unknown, and are learnt from the data, along with the posterior mean and covariance... (read more)

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  • NUMERICAL ANALYSIS
  • NUMERICAL ANALYSIS
  • STATISTICS THEORY
  • STATISTICS THEORY