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新方法描述了MMD泛函的Wasserstein梯度流

研究人员开发了一种方法,使用负距离核来描述最大均值差异(MMD)泛函的Wasserstein梯度流。该方法通过解决分位数函数(Wasserstein-2空间的嵌入)上的相关Cauchy问题来表征这些流。该研究为该Cauchy问题提供了一个解,为离散目标测度提供了一个分段线性公式,并证明了流的不变性和平滑性。 AI

排序理由 该集群包含一篇学术论文,详细介绍了一种分析梯度流的新数学方法。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv stat.ML 阅读 →

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新方法描述了MMD泛函的Wasserstein梯度流

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该集群包含一篇学术论文,详细介绍了一种分析梯度流的新数学方法。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Richard Duong, Viktor Stein, Robert Beinert, Johannes Hertrich, Gabriele Steidl ·

    带距离核的MMD泛函的Wasserstein梯度流与分位数函数上的Cauchy问题

    arXiv:2408.07498v5 Announce Type: replace-cross Abstract: We give a comprehensive description of Wasserstein gradient flows of maximum mean discrepancy (MMD) functionals $\mathcal F_\nu := \text{MMD}_K^2(\cdot, \nu)$ towards given target measures $\nu$ on the real line, where we …