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Autoencoders vs. Numerical Analysis--Informed Manifold Learning for Navier--Stokes Flows
Autoencoders (AEs) have become a dominant approach to nonlinear latent-space construction in data-driven reduced-order modelling (ROM), with their decoders lifting latent representations back to the ambient state space. Their prominence, however, has overshadowed an established alternative: manifold
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