1 citations · 1 across the 4 of their papers we have counts for
5 papers
PDE-constrained Gaussian process surrogate modeling with uncertain data locations
Dongwei Ye, Weihao Yan, Christoph Brune +1
Gaussian process regression is widely applied in computational science and engineering for surrogate modeling owning to its kernel-based and probabilistic nature. In this work, we…
Data-driven reduced-order modelling for blood flow simulations with geometry-informed snapshots
Dongwei Ye, Valeria Krzhizhanovskaya, Alfons G. Hoekstra
Parametric reduced-order modelling often serves as a surrogate method for hemodynamics simulations to improve the computational efficiency in many-query scenarios or to perform rea…
Inverse uncertainty quantification of a mechanical model of arterial tissue with surrogate modeling
Salome Kakhaia, Pavel Zun, Dongwei Ye +1
Disorders of coronary arteries lead to severe health problems such as atherosclerosis, angina, heart attack and even death. Considering the clinical significance of coronary arteri…
Uncertainty quantification of a three-dimensional in-stent restenosis model with surrogate modelling
Dongwei Ye, Pavel Zun, Valeria Krzhizhanovskaya +1
In-Stent Restenosis is a recurrence of coronary artery narrowing due to vascular injury caused by balloon dilation and stent placement. It may lead to the relapse of angina symptom…
Non-intrusive and semi-intrusive uncertainty quantification of a multiscale in-stent restenosis model
Dongwei Ye, Anna Nikishova, Lourens Veen +2
Uncertainty estimations are presented of the response of a multiscale in-stent restenosis model, as obtained by both non-intrusive and semi-intrusive uncertainty quantification. Th…