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English(EN) Data-driven discovery of intrinsic Lie point symmetries of differential equation systems

新方法从数据中发现微分方程的李对称性

研究人员开发了一种新颖的数据驱动方法来发现微分方程系统中的连续对称性。该方法绕过了符号确定方程或系统完整闭式表示的需要,而是将对称性发现视为采样喷射空间数据上的算子理论问题。该框架结合了延拓、子空间限制和非线性字典来识别可容许生成元及其李括号结构,并在具有已知 11 维对称代数的基准测试中取得了成功。 AI

影响 该方法可以通过揭示复杂系统中隐藏的结构,从而实现更有效的模型降维并增强科学机器学习。

排序理由 该集群包含一篇学术论文,详细介绍了使用数据驱动技术发现微分方程对称性的新方法。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新方法从数据中发现微分方程的李对称性

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该集群包含一篇学术论文,详细介绍了使用数据驱动技术发现微分方程对称性的新方法。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ilker Gurcan, Kadir Ustun, Ramazan Gokberk Cinbis ·

    数据驱动的微分方程组内在李点对称性发现

    arXiv:2611.08421v1 Announce Type: new Abstract: Discovering continuous symmetries directly from differential-equation data can reveal geometric structure for model reduction and scientific machine learning without symbolic determining equations or a closed-form representation of …