179 citations · 186 across the 4 of their papers we have counts for
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cond-mat.mtrl-sci2018★ 179 cited
Machine-learned multi-system surrogate models for materials prediction
Chandramouli Nyshadham, Matthias Rupp, Brayden Bekker +6
Surrogate machine-learning models are transforming computational materials science by predicting properties of materials with the accuracy of ab initio methods at a fraction of the…
cs.CE2018★ 7 cited
Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications
A. Hunter, B. A. Moore, M. K. Mudunuru +9
In this paper, five different approaches for reduced-order modeling of brittle fracture in geomaterials, specifically concrete, are presented and compared. Four of the five methods…