Cross-Domain Pretraining for Steady-State Neural CFD Surrogates
This work finds that cross-domain pretraining improves zero- and few-shot performance on held-out datasets relative to both training from scratch and transferring from domain-specific experts, and finds that simply pooling steady-state datasets is both sufficient and effective.
Anthony Zhou, A. Farimani, Shirley Ho et al.
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