12 citations · 14 across the 7 of their papers we have counts for
3 papers · 1 filter
Uncertainty Quantification of Engineering Structures by Polynomial Chaos Expansion and Multivariate Active Learning
Qitian Lu, Jafar Jafari-Asl, Panagiotis Spyridis +1
In many engineering applications, a single high-fidelity model produces multiple quantities of interest (QoIs) under the same input parameters, e.g. finite element models of comple…
Physics-Informed Polynomial Chaos Expansions
Lukáš Novák, Himanshu Sharma, Michael D. Shields
Surrogate modeling of costly mathematical models representing physical systems is challenging since it is typically not possible to create a large experimental design. Thus, it is…
Active Learning-based Domain Adaptive Localized Polynomial Chaos Expansion
Lukáš Novák, Michael D. Shields, Václav Sadílek +1
The paper presents a novel methodology to build surrogate models of complicated functions by an active learning-based sequential decomposition of the input random space and constru…