3 papers
stat.ME2026
Diffeomorphic registration distances for Bayesian calibration of infinite-dimensional computer models
Paul Lartaud, Gwenaël Salin
The simulation of physical phenomena with computer models relies on the estimation of physical and/or numerical parameters calibrated to fit experimental data. The approximations w…
stat.ME2025
Sequential design for surrogate modeling in Bayesian inverse problems
Paul Lartaud, Philippe Humbert, Josselin Garnier
Sequential design is a highly active field of research in active learning which provides a general framework for designing computer experiments with limited computational budgets.…
stat.AP2024
Uncertainty quantification in neutron and gamma time correlation measurements
Paul Lartaud, Philippe Humbert, Josselin Garnier
Neutron noise analysis is a predominant technique for fissile matter identification with passive methods. Quantifying the uncertainties associated with the estimated nuclear parame…