Spatio-Temporal Forecasting and Uncertainty Quantification of COVID-19 Cases in Shanghai via a Bayesian Deep Learning Approach

Spatio-Temporal Forecasting and Uncertainty Quantification of COVID-19 Cases in Shanghai via a Bayesian Deep Learning Approach

ZHOU Shirong, TANG Yincai, WANG Pingping, ZHUANG Liangliang, XU Jiawei

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CHINESE JOURNAL OF APPLIED PROBABILITY AND STATISTICS ›› 2024, Vol. 40 ›› Issue (2) : 298-322. DOI: 10.3969/j.issn.1001-4268.2024.02.006

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Spatio-Temporal Forecasting and Uncertainty Quantification of COVID-19 Cases in Shanghai via a Bayesian Deep Learning Approach

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{{article.zuoZheEn_L}}. {{article.title_en}}. {{journal.qiKanMingCheng_EN}}. 2024, 40(2): 298-322 https://doi.org/10.3969/j.issn.1001-4268.2024.02.006

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