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20172026
most citedData-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold

59 citations · 109 across the 17 of their papers we have counts for

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Showing 2021Show all

2 papers · 1 filter

physics.bio-ph2021★ 15 cited

Data-driven Uncertainty Quantification in Computational Human Head Models

Kshitiz Upadhyay, Dimitris G. Giovanis, Ahmed Alshareef +6

Computational models of the human head are promising tools for estimating the impact-induced response of brain, and thus play an important role in the prediction of traumatic brain…

physics.data-an2021★ 10 cited

Grassmannian diffusion maps based surrogate modeling via geometric harmonics

Ketson R. M. dos Santos, Dimitrios G. Giovanis, Katiana Kontolati +2

In this paper, a novel surrogate model based on the Grassmannian diffusion maps (GDMaps) and utilizing geometric harmonics is developed for predicting the response of engineering s…