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English(EN) Gauss--Hermite Quadrature for Gaussian-Mixture Entropy with an Action-Space Hermite Surrogate

新的高斯-厄米积分方法用于高斯混合熵

研究人员开发了一种新的高斯-厄米积分方法,用于数值逼近高斯混合的微分熵,高斯混合通常缺乏闭式解。该方法的准确性受积分阶数的影响,并在一个和两个维度上通过基准进行了验证。此外,对于连续作用优化,引入了作用空间中的厄米多项式代理,与传统的泰勒代理相比,在雷达指向基准中显示出更低的误差和遗憾。 AI

排序理由 该集群包含一篇学术论文,详细介绍了一种新的微分熵逼近数值方法。[lever_c_research降级:ic=1 ai=0.7]

在 arXiv stat.ML 阅读 →

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新的高斯-厄米积分方法用于高斯混合熵

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该集群包含一篇学术论文,详细介绍了一种新的微分熵逼近数值方法。[lever_c_research降级:ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Jae Wan Shim ·

    高斯-埃尔米特求积法用于具有作用空间埃尔米特代理的高斯混合熵

    arXiv:2608.21467v1 Announce Type: new Abstract: Gaussian distributions are used to model uncertainty in signals and states, and Gaussian mixtures are often used when the underlying distribution is multimodal. Unlike a single Gaussian, a Gaussian mixture generally has no closed-fo…