13 citations · 13 across the 1 of their papers we have counts for
5 papers · 1 filter
Bayesian model inversion using stochastic spectral embedding
P. -R. Wagner, S. Marelli, B. Sudret
In this paper we propose a new sampling-free approach to solve Bayesian model inversion problems that is an extension of the previously proposed spectral likelihood expansions (SLE…
Stochastic spectral embedding
S. Marelli, P. -R. Wagner, C. Lataniotis +1
Constructing approximations that can accurately mimic the behavior of complex models at reduced computational costs is an important aspect of uncertainty quantification. Despite th…
Development of probabilistic dam breach model using Bayesian inference
S. J. Peter, A. Siviglia, J. Nagel +4
Dam breach models are commonly used to predict outflow hydrographs of potentially failing dams and are key ingredients for evaluating flood risk. In this paper a new dam breach mod…
Hierarchical Kriging for multi-fidelity aero-servo-elastic simulators - Application to extreme loads on wind turbines
I. Abdallah, C. Lataniotis, B. Sudret
In the present work, we consider multi-fidelity surrogate modelling to fuse the output of multiple aero-servo-elastic computer simulators of varying complexity. In many instances,…
Metamodel-based sensitivity analysis: Polynomial chaos expansions and Gaussian processes
L. Le Gratiet, S. Marelli, B. Sudret
Global sensitivity analysis is now established as a powerful approach for determining the key random input parameters that drive the uncertainty of model output predictions. Yet th…