4 citations · 5 across the 3 of their papers we have counts for
3 papers
stat.ML2022
Learning Physics between Digital Twins with Low-Fidelity Models and Physics-Informed Gaussian Processes
Michail Spitieris, Ingelin Steinsland
A digital twin is a computer model that represents an individual, for example, a component, a patient or a process. In many situations, we want to gain knowledge about an individua…
stat.ME2022★ 1 cited
Bayesian calibration of Arterial Windkessel Model
Michail Spitieris, Ingelin Steinsland, Emma Ingestrom
This work is motivated by personalized digital twins based on observations and physical models for treatment and prevention of Hypertension. The models commonly used are simplifica…
stat.ML2022★ 4 cited
Bayesian Calibration of Imperfect Computer Models using Physics-Informed Priors
Michail Spitieris, Ingelin Steinsland
We introduce a computational efficient data-driven framework suitable for quantifying the uncertainty in physical parameters and model formulation of computer models, represented b…