A review of multi-fidelity surrogates from co-kriging to neural networks for composite mechanics, with applications in prediction, optimization, and workflow integration.
Predicting the output from a complex computer code when fast approximations are available.Biometrika, 87(1):1–13, 03 2000
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Multi-fidelity surrogates for mechanics of composites: from co-kriging to multi-fidelity neural networks
A review of multi-fidelity surrogates from co-kriging to neural networks for composite mechanics, with applications in prediction, optimization, and workflow integration.