Guillaume Perrin

A variance-based framework for robust variable selection under correlated inputs and unobserved factors

Calibration of sensors in partially observed and correlated environments raises fundamental challenges for variable selection and model interpretation. When observations are noisy and influenced by unmeasured factors, classical selection criteria based on regression coefficients,...

Sequential Bayesian identification using multi-fidelity Gaussian process surrogates: Application to an inverse transient thermal problem

A sequential Bayesian inversion algorithm is proposed for the estimation of unknown parameters in complex physical models, particularly when dealing with expensive simulations, a frequent challenge in industrial applications. The approach aims to accurately infer the posterior di...