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English(EN) Discovering Multiscale Deep Formulas in Complex Systems via Neural-Guided Lambda Calculus

AI方法Deflex从复杂系统中提取多尺度公式

研究人员开发了一种名为Deflex的AI方法,旨在从复杂系统中提取数学公式,特别是那些具有多个尺度的系统。该方法利用一个神经引导的Lambda演算系统,结合符号回归模型和深度能量模型来识别特定尺度的模式。据报道,Deflex在发现这些多尺度公式方面比现有方法具有更高的效率,为科学发现提供了潜在工具。 AI

影响 能够自动化发现复杂系统中的基本数学定律,有可能加速跨学科的科学突破。

排序理由 该集群包含一篇详细介绍一种新AI方法的学术论文,用于科学发现。

在 arXiv cs.LG 阅读 →

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AI方法Deflex从复杂系统中提取多尺度公式

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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Hanqiao Yu, Shusen Yang, Xuebin Ren, Cong Zhao ·

    通过神经引导的Lambda演算在复杂系统中发现多尺度深度公式

    arXiv:2606.07426v1 Announce Type: new Abstract: A fundamental problem in science is identifying underlying patterns of complex systems in the form of concise mathematical formulas. Current Artificial Intelligence (AI)-based methods have shown strong performance in single-scale sy…

  2. arXiv cs.LG TIER_1 English(EN) · Cong Zhao ·

    通过神经引导的Lambda演算在复杂系统中发现多尺度深度公式

    A fundamental problem in science is identifying underlying patterns of complex systems in the form of concise mathematical formulas. Current Artificial Intelligence (AI)-based methods have shown strong performance in single-scale systems, yet remain limited in identifying scale-s…