Bayesian Posterior Perturbation Analysis with Integral Probability Metrics

no code implementations • 2 Mar 2023 • Alfredo Garbuno-Inigo, Tapio Helin, Franca Hoffmann, Bamdad Hosseini

In recent years, Bayesian inference in large-scale inverse problems found in science, engineering and machine learning has gained significant attention.

Bayesian Inference

Calibration and Uncertainty Quantification of Convective Parameters in an Idealized GCM

no code implementations • 24 Dec 2020 • Oliver R. A. Dunbar, Alfredo Garbuno-Inigo, Tapio Schneider, Andrew M. Stuart

Here we demonstrate an approach to model calibration and uncertainty quantification that requires only $O(10^2)$ model runs and can accommodate internal climate variability.

Gaussian Processes Statistics Theory Statistics Theory