1 code implementation • 15 Jan 2024 • Edgar Jaber, Vincent Blot, Nicolas Brunel, Vincent Chabridon, Emmanuel Remy, Bertrand Iooss, Didier Lucor, Mathilde Mougeot, Alessandro Leite
Gaussian processes (GPs) are a Bayesian machine learning approach widely used to construct surrogate models for the uncertainty quantification of computer simulation codes in industrial applications.
3 code implementations • 25 Jul 2022 • Vianney Taquet, Vincent Blot, Thomas Morzadec, Louis Lacombe, Nicolas Brunel
Estimating uncertainties associated with the predictions of Machine Learning (ML) models is of crucial importance to assess their robustness and predictive power.