BriefGPT.xyz
May, 2023
深度学习和MCMC与aggVAE用于调整行政边界: 在肯尼亚绘制疟疾流行地图
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in Kenya
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Elizaveta Semenova, Swapnil Mishra, Samir Bhatt, Seth Flaxman, H Juliette T Unwin
TL;DR
通过结合深度生成建模和完全贝叶斯推断的方法,我们解决了基于行政单元的空间相关性模型在行政边界变化时所面临的支持变化问题,从而更好地绘制肯尼亚疟疾患病率地图。
Abstract
Model-based
disease mapping
remains a fundamental policy-informing tool in public health and disease surveillance with
hierarchical bayesian models
being the current state-of-the-art approach. When working with a
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