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Functional principal component analysis for global sensitivity analysis of model with spatial output.

, , , , , , , , and . Reliab. Eng. Syst. Saf., (2021)

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Uncertainties in conditional probability tables of discrete Bayesian Belief Networks: A comprehensive review.. Eng. Appl. Artif. Intell., (2020)Sensitivity analysis of Bayesian networks to parameters of the conditional probability model using a Beta regression approach., and . Expert Syst. Appl., (2020)Global sensitivity analysis of large-scale numerical landslide models based on Gaussian-Process meta-modeling., and . Comput. Geosci., 37 (7): 917-927 (2011)Gaussian process metamodeling of functional-input code for coastal flood hazard assessment., , , , , and . Reliab. Eng. Syst. Saf., (2020)FunQuant: A R package to perform quantization in the context of rare events and time-consuming simulations., , , , , and . CoRR, (2023)Functional principal component analysis for global sensitivity analysis of model with spatial output., , , , , , , , and . Reliab. Eng. Syst. Saf., (2021)Profile Extrema for Visualizing and Quantifying Uncertainties on Excursion Regions: Application to Coastal Flooding., , , and . Technometrics, 61 (4): 474-493 (2019)Multi-Output Gaussian Processes with Functional Data: A Study on Coastal Flood Hazard Assessment., , , and . CoRR, (2020)Multioutput Gaussian processes with functional data: A study on coastal flood hazard assessment., , , and . Reliab. Eng. Syst. Saf., 218 (Part): 108139 (2022)Revealing the interlevel dependence structure of categorical inputs in numerical environmental simulations with kernel model selection., , , and . Environ. Model. Softw., (2022)