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2104.02650
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Model-data-driven constitutive responses: application to a multiscale computational framework
6 April 2021
J. Fuhg
C. Boehm
N. Bouklas
A. Fau
P. Wriggers
M. Marino
AILaw
AI4CE
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Papers citing
"Model-data-driven constitutive responses: application to a multiscale computational framework"
4 / 4 papers shown
Title
EquiNO: A Physics-Informed Neural Operator for Multiscale Simulations
Hamidreza Eivazi
Jendrik-Alexander Tröger
Stefan H. A. Wittek
Stefan Hartmann
Andreas Rausch
AI4CE
112
1
0
27 Mar 2025
Interval and fuzzy physics-informed neural networks for uncertain fields
J. Fuhg
Ioannis Kalogeris
A. Fau
N. Bouklas
AI4CE
97
19
0
18 Jun 2021
Local approximate Gaussian process regression for data-driven constitutive laws: Development and comparison with neural networks
J. Fuhg
M. Marino
N. Bouklas
80
61
0
07 May 2021
The mixed deep energy method for resolving concentration features in finite strain hyperelasticity
J. Fuhg
N. Bouklas
PINN
AI4CE
81
95
0
15 Apr 2021
1