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Reducing Training Complexity in Empirical Quadrature-Based Model Reduction via Structured Compression
Model order reduction seeks to approximate large-scale dynamical systems by lower-dimensional reduced models. For linear systems, a small reduced dimension directly translates into low computational cost, ensuring online efficiency. This property does not generally hold for nonlinear systems, where
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