Multifidelity Prediction Framework with Convolutional Neural Networks Using High-Dimensional Data

What is it about?

The neural network architectures that we propose are usable for high-dimensional data with two different physical accuracies. We try to enhance the prediction accuracy of the surrogate model by implementing additional networks. The presented method diminishes the computational effort dramatically while keeping the accuracy as high as in the higher accuracy solver data.

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