Gaussian process (GP) regression is a popular surrogate modeling tool for computer simulations in engineering and scientific domains. However, it often struggles with high computational costs and low ...
Gaussian process (GP) regression is a popular surrogate modeling tool for computer simulations in engineering and scientific domains. However, it often struggles with high computational costs and low ...
Combining low-fidelity trend information with empirical data to train models can improve their accuracy and reduce costs.
The big news from COMSOL 6.2, released this week, is that engineers will be able to replace their complex, 3D finite element simulations with surrogate models based on machine learning technology.
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