Program (detailed contents):
* Introduction: computer experiments and metamodeling. Examples.
* Metamodeling with Gaussian process (GP) and kriging. a) Probabilistic and functional (RKHS) interpretation of the approximation problem. b) Simulation of GPs. c) Customization of covariance models. Physically informed GPs.
* Design of computer experiments. a) Initial designs: focus on space-filling designs. b) Adaptive methods. Example of Bayesian optimisation.
* Uncertainty quantification. a) Uncertainty propagation. b) Global sensitivity analysis: focus on the ANOVA decomposition (Sobol-Hoeffding decomposition).
* Case study.
