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How Spatial Scientists Are Solving the Gaussian Process Scaling Challenge

Summary by unsafe.sh
本文探讨了处理大规模空间数据的方法，包括低秩近似、协方差 tapering、分治策略和 Vecchia 近似等技术。Vecchia 近似通过因子分解简化条件分布，在并行计算中表现出色，并被扩展用于贝叶斯推理。文章还讨论了 MCMC 方法的计算成本问题及近期的子采样方法。
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How Spatial Scientists Are Solving the Gaussian Process Scaling Challenge

本文探讨了处理大规模空间数据的方法，包括低秩近似、协方差 tapering、分治策略和 Vecchia 近似等技术。Vecchia 近似通过因子分解简化条件分布，在并行计算中表现出色，并被扩展用于贝叶斯推理。文章还讨论了 MCMC 方法的计算成本问题及近期的子采样方法。

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unsafe.sh broke the news in on Saturday, May 31, 2025.
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