Search
Results
-
Stochastic spectral likelihood embedding for the calibration of heat transfer models
(2021)Other Conference Item -
An adaptive algorithm based on spectral likelihood expansion for efficient Bayesian calibration
(2019)Other Conference Item -
Surrogate models for uncertainty quantification and design optimization
(2019)Nowadays computational models are used in virtually all fields of applied sciences and engineering to predict the behaviour of complex natural or man-made systems. Also known as simulators, they allow the engineer to assess the performance of a system in-silico, and then optimize its design or operating. Realistic models (e.g. finite element models) usually feature tens of parameters and are costly to run, even when taking full advantage ...Other Conference Item -
-
A new approach for Bayesian model calibration using stochastic spectral embedding
(2019)Other Conference Item