Uncertainty analysis of deterministic models with Gaussian process approximation

Approach to solve the problems of uncertainty analysis of deterministic models based on Gaussian random fields is introduced. To construct the regressions of different models covariance functions with some common hyperparameters are used. We consider the practical examples of data on nuclear reactions, as well as the problem of non-stationary time series clustering.