Transfer Learning for Flow Reconstruction Based on Multifidelity Data

Reduced-order modeling for multifidelity flow reconstruction offers increased accuracy while saving cost in data generation. The key to obtaining successful multifidelity models lies in properly capturing the correlation between low-fidelity and high-fidelity data. In this work, we propose to apply...

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