The spatially and temporally variable parameters and inputs to complex groundwater
models typically result in long runtimes which hinder comprehensive calibration, sensitivity …

In this paper we present a basis selection method that can be used with ℓ 1-minimization to
adaptively determine the large coefficients of polynomial chaos expansions (PCE). The …

We propose an adaptive sparse grid stochastic collocation approach based upon Leja
interpolation sequences for approximation of parameterized functions with high-dimensional …

In this paper, we present an adaptive algorithm to construct response surface
approximations of high‐fidelity models using a hierarchy of lower fidelity models. Our …

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 …

Science and Engineering applications are typically associated with expensive optimization
problem to identify optimal design solutions and states of the system of interest. Bayesian …

We present an adaptive algorithm for constructing surrogate models of multi‐disciplinary
systems composed of a set of coupled components. With this goal we introduce “coupling” …

We propose a multi-element stochastic collocation method that can be applied in high-
dimensional parameter space for functions with discontinuities lying along manifolds of …

Sparse-grid methods have recently gained interest in reducing the computational cost of
solving high-dimensional kinetic equations. In this paper, we construct adaptive and hybrid …

Predictive analysis of complex computational models, such as uncertainty quantification
(UQ), must often rely on using an existing database of simulation runs. In this paper we …