A language model-based operator learning method reconstructs flow fields from under 10% sparse measurements on vortex street, US temperature, blood flow, and turbulent jet benchmarks with competitive accuracy.
Blending neural operators and relaxation methods in pde numerical solvers.Nature Machine Intelligence, pages 1–11
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Operator Learning for Reconstructing Flow Fields from Sparse Measurements: a Language Model Approach
A language model-based operator learning method reconstructs flow fields from under 10% sparse measurements on vortex street, US temperature, blood flow, and turbulent jet benchmarks with competitive accuracy.