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

59 citations · 59 across the 1 of their papers we have counts for

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math.NA2020★ 59 cited

Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold

Dimitris G. Giovanis, Michael D. Shields

This paper introduces a surrogate modeling scheme based on Grassmannian manifold learning to be used for cost-efficient predictions of high-dimensional stochastic systems. The meth…