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A finite operator learning technique for mapping the elastic properties of microstructures to their mechanical deformations
Our method, inspired by operator learning and the finite element method, demonstrates the ability to train without relying on data from other numerical solvers.
Integration of physics-informed operator learning and finite element method for parametric learning of partial differential equations
We benchmark our methodology against the standard finite element method, demonstrating accurate yet faster predictions using the trained neural network for temperature and flux profiles.
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