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English(EN) Bayesian inverse problems and epidemic-threshold uncertainty for a heterogeneous SIS reaction-diffusion model

新的贝叶斯方法从早期数据推断流行病持续性

研究人员开发了一种新方法,可以从异构SIS反应扩散模型的早期观测中推断流行病的持续性。研究表明,关键的流行病动力学取决于传播率与恢复率之差以及感染者的扩散性。该论文还建立了SIS系统的贝叶斯适定性,并提供了说明阈值推断和收敛速度的数值示例。 AI

排序理由 该集群包含一篇在arXiv上发表的学术论文。[lever_c_demoted from research: ic=1 ai=0.0]

在 arXiv cs.LG 阅读 →

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新的贝叶斯方法从早期数据推断流行病持续性

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该集群包含一篇在arXiv上发表的学术论文。[lever_c_demoted from research: ic=1 ai=0.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Duc-Lam Duong ·

    贝叶斯逆问题与异质SIS反应-扩散模型的流行病阈值不确定性

    arXiv:2611.14468v1 Announce Type: cross Abstract: We study Bayesian inference of persistence from early observations of a heterogeneous susceptible--infected--susceptible (SIS) reaction--diffusion model with standard incidence. We show that the leading prevalence dynamics depend …