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MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems
arXiv:2604.06881v2 Announce Type: replace Abstract: Neural operators have emerged as powerful surrogates for dynamical systems due to their grid-invariant properties and computational efficiency. However, Fourier-based variants inherently truncate high-frequency components in spectral space, resulting in the loss of small-scale structures and degraded prediction quality at high resolutions when trained on low-resolution data.
MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems
arXiv:2604.06881v2 Announce Type: replace-cross Abstract: Neural operators have emerged as powerful surrogates for dynamical systems due to their grid-invariant properties and computational efficiency. However, Fourier-based variants inherently truncate high-frequency components in spectral space, resulting in the loss of small-scale structures and degraded prediction quality at high resolutions when trained on low-resolution data.
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