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OPINE: Orthogonal Projection in Invertible Nonlinear Embeddings for Turbulent Flows
Proper orthogonal decomposition (POD) represents physical fields with orthogonal modes ordered by variance, so that one decomposition gives reduced coordinates in every dimension, but it needs many modes when the data lie near a curved manifold. Nonlinear autoencoders are more compact, but their inf
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