most citedLearning Nonlinear Projections for Reduced-Order Modeling of Dynamical Systems using Constrained Autoencoders

2 citations · 2 across the 1 of their papers we have counts for

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math.DS2023★ 2 cited

Learning Nonlinear Projections for Reduced-Order Modeling of Dynamical Systems using Constrained Autoencoders

Samuel E. Otto, Gregory R. Macchio, Clarence W. Rowley

Recently developed reduced-order modeling techniques aim to approximate nonlinear dynamical systems on low-dimensional manifolds learned from data. This is an effective approach fo…