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English(EN) Expected Signature Kernels for Rough Paths

新方法表征 Lévy 粗糙路径的预期签名核

研究人员开发了一种表征 Lévy 粗糙路径预期签名核的方法,这是一种路径空间上概率律的相似性度量。这项工作建立在先前研究的基础上,为这些核提供了一种新的描述,特别是在 Goursat 型系统的背景下。该研究详细介绍了如何处理连续和跳跃过程,为后者提供具有误差控制的有限维截断。此外,该论文还提出了一种推导条件高斯鞅签名-MMD 检验的无偏统计量的方法,通过可计算的有限网格版本展示了方差缩减和功率增强。 AI

排序理由 该条目是发表在 arXiv 上的研究论文,详细介绍了数学方法。[lever_c_demoted from research: ic=1 ai=0.1]

在 arXiv stat.ML 阅读 →

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新方法表征 Lévy 粗糙路径的预期签名核

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该条目是发表在 arXiv 上的研究论文,详细介绍了数学方法。[lever_c_demoted from research: ic=1 ai=0.1]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Peter K. Friz, Paul P. Hager ·

    预期中的粗糙路径签名核

    arXiv:2509.07893v2 Announce Type: replace-cross Abstract: The expected signature kernel is a similarity measure of probability laws on path space and enters directly into signature maximum mean discrepancies. Building on [P. K. Friz, P. P. Hager, and N. Tapia, Forum Math. Sigma, …