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Local approximate Gaussian process regression for data-driven constitutive laws: Development and comparison with neural networks
Hierarchical computational methods for multiscale mechanics such as the FE$^2$ and FE-FFT methods are generally accompanied by high computational costs.
Model-data-driven constitutive responses: application to a multiscale computational framework
Computational multiscale methods for analyzing and deriving constitutive responses have been used as a tool in engineering problems because of their ability to combine information at different length scales.
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