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Multilevel Neural Corrections with Adaptive Sampling for Partial Differential Equations
We propose a multi-level framework for deep neural PDE solvers that integrates adaptive sampling with additive neural corrections. At each level, an adaptive sampling distribution is constructed from normalized residual-gradient indicators inherited from the preceding levels, thereby concentrating c
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