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English(EN) Diffusion models for the $O(3)$ nonlinear sigma model

扩散模型应用于 O(3) 非线性西格玛模型

研究人员开发了一种基于分数的扩散模型来分析二维经典海森堡模型,该模型代表 O(3) 非线性西格玛模型。该方法利用通过在不同数据粗粒度上训练的神经网络实现的が多尺度采样方案,旨在提高采样精度和计算效率。该研究还引入了 Stein 诊断来评估学习到的分数的质量,并讨论了将扩散模型应用于球体的技术考虑,包括输入提升和边界层近似。 AI

影响 展示了扩散模型在物理模拟中的新应用,有望提高复杂模型的计算效率。

排序理由 学术论文,详细介绍了扩散模型在物理问题中的新颖应用。[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 →

扩散模型应用于 O(3) 非线性西格玛模型

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学术论文,详细介绍了扩散模型在物理问题中的新颖应用。[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) · Daniel Schubring ·

    $O(3)$ 非线性西格玛模型中的扩散模型

    arXiv:2610.39568v2 Announce Type: replace-cross Abstract: A score-based diffusion model is trained on the two-dimensional classical Heisenberg model, the lattice representation of the $O(3)$ nonlinear sigma model. Neural networks are trained on three different coarse-grainings of…