English(EN) When Does Jacobian Fine-Tuning Stabilize Neural PDE Emulators?

Jacobian 微调稳定神经偏微分方程模拟器

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

一篇新的研究论文探讨了 Jacobian 微调作为一种稳定混沌偏微分方程（PDE）神经模拟器的方法。该研究将误差来源分解，区分了物理误差增长和模型引起的误差放大。通过将模拟器误差与通过求解器 Jacobian 传播错误的对立情景进行比较，研究人员推导出了放大率。该放大率有助于确定 Jacobian 微调显著减少了误差，特别是对于放大率较高的模型，其收益与微调成本和放大率相关。 AI

影响引入了一种提高用于模拟复杂物理系统的神经网络可靠性的技术。

排序理由关于稳定神经网络模拟器新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Shreeyam Bangera, Manya Gupta · 2026-11-02 05:00

When Does Jacobian Fine-Tuning Stabilize Neural PDE Emulators?

arXiv:2610.42013v1 Announce Type: new Abstract: Neural emulators of chaotic PDEs are trained on one-step prediction but deployed autoregressively, where their errors compound. Jacobian-based regularisers aim to curb this growth, but in a chaotic system part of the growth is physi…

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When Does Jacobian Fine-Tuning Stabilize Neural PDE Emulators?

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