Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control

Armin Lederer, Jonas Umlauft, Sandra Hirche

Neural Information Processing Systems 

Key to the application of such models in safety-critical domains is the quantification of their model error. Gaussian processes provide such a measure anduniform error bounds havebeen derived,which allowsafe control based on thesemodels.

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