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Variance based sensitivity analysis for Monte Carlo and importance sampling reliability assessment with Gaussian processes., , , , , and . CoRR, (2020)A mixed-categorical correlation kernel for Gaussian process., , , , and . Neurocomputing, (2023)Adaptive coupling of reduced basis modeling and Kriging based active learning methods for reliability analyses., , , , and . Reliab. Eng. Syst. Saf., (2020)SMT 2.0: A Surrogate Modeling Toolbox with a focus on Hierarchical and Mixed Variables Gaussian Processes., , , , , , , , and . CoRR, (2023)Optimisation adaptative basée sur les métamodèles. (Surrogate-based and adaptive optimization).. (2019)High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft., , , , and . CoRR, (2023)An efficient application of Bayesian optimization to an industrial MDO framework for aircraft design., , , , , and . CoRR, (2020)Upper Trust Bound Feasibility Criterion for Mixed Constrained Bayesian Optimization with Application to Aircraft Design., , , and . CoRR, (2020)SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes., , , , , , , , and . Adv. Eng. Softw., (February 2024)A Python surrogate modeling framework with derivatives., , , , , and . Adv. Eng. Softw., (2019)