5 papers
Calibration and Uncertainty Quantification of Convective Parameters in an Idealized GCM
Oliver R. A. Dunbar, Alfredo Garbuno-Inigo, Tapio Schneider +1
Parameters in climate models are usually calibrated manually, exploiting only small subsets of the available data. This precludes both optimal calibration and quantification of unc…
History matching with probabilistic emulators and active learning
Alfredo Garbuno-Inigo, F. Alejandro DiazDelaO, Konstantin M. Zuev
The scientific understanding of real-world processes has dramatically improved over the years through computer simulations. Such simulators represent complex mathematical models th…
Calibrate, Emulate, Sample
Emmet Cleary, Alfredo Garbuno-Inigo, Shiwei Lan +2
Many parameter estimation problems arising in applications are best cast in the framework of Bayesian inversion. This allows not only for an estimate of the parameters, but also fo…
Affine invariant interacting Langevin dynamics for Bayesian inference
Alfredo Garbuno-Inigo, Nikolas Nüsken, Sebastian Reich
We propose a computational method (with acronym ALDI) for sampling from a given target distribution based on first-order (overdamped) Langevin dynamics which satisfies the property…
Interacting Langevin Diffusions: Gradient Structure And Ensemble Kalman Sampler
Alfredo Garbuno-Inigo, Franca Hoffmann, Wuchen Li +1
Solving inverse problems without the use of derivatives or adjoints of the forward model is highly desirable in many applications arising in science and engineering. In this paper,…