[论文] Error-Conditioned Neural Solvers

论文概要

研究领域: CV
作者: Haina Jiang, Liam Wang, Peng-Chen Chen
发布时间: 2026-06-27
arXiv: 2606.27354

中文摘要

Neural surrogate models offer fast approximate mappings from PDE parameters to solutions, but they typically treat solving as a purely statistical task: once trained, they struggle to correct their own constraint violations and extrapolate beyond the training distribution. Recent hybrid methods prom...

原文摘要

Neural surrogate models offer fast approximate mappings from PDE parameters to solutions, but they typically treat solving as a purely statistical task: once trained, they struggle to correct their own constraint violations and extrapolate beyond the training distribution. Recent hybrid methods promote physical correctness by targeting the PDE residual via gradient descent or Gauss--Newton steps, but inherit the compute cost and instability of the underlying classical optimizers. We show, theore...

自动采集于 2026-06-27

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