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This paper deals with the evaluation of double line integrals of the squaredexponential covariance function. We propose a new approach in which the doubleintegral is reduced to a single integral using the error function. This singleintegral is then computed with efficiently implemented numerical techniques.The performance is compared against existing state of the art methods and theresults show superior properties in numerical robustness and accuracy percomputation time.

Evaluating the squared-exponential covariance function in Gaussian processes with integral observations