115 citations · 184 across the 5 of their papers we have counts for
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cond-mat.soft2024★ 2 cited
Polyconvex neural network models of thermoelasticity
Jan N. Fuhg, Asghar Jadoon, Oliver Weeger +2
Machine-learning function representations such as neural networks have proven to be excellent constructs for constitutive modeling due to their flexibility to represent highly nonl…
cond-mat.soft2023★ 1 cited
Stress representations for tensor basis neural networks: alternative formulations to Finger-Rivlin-Ericksen
Jan N. Fuhg, Nikolaos Bouklas, Reese E. Jones
Data-driven constitutive modeling frameworks based on neural networks and classical representation theorems have recently gained considerable attention due to their ability to easi…