An approximate greedy router for hybrid PDE solvers that mimics optimal selection without true error access and shows faster, more stable error reduction on test equations.
Mitigating spectral bias in neural operators via high-frequency scaling for physical systems.arXiv preprint arXiv:2503.13695
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A Greedy PDE Router for Blending Neural Operators and Classical Methods
An approximate greedy router for hybrid PDE solvers that mimics optimal selection without true error access and shows faster, more stable error reduction on test equations.
- MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems