20 citations · 21 across the 2 of their papers we have counts for
5 papers
Quantifying Uncertainty in Deep Spatiotemporal Forecasting
Dongxia Wu, Liyao Gao, Xinyue Xiong +4
Deep learning is gaining increasing popularity for spatiotemporal forecasting. However, prior works have mostly focused on point estimates without quantifying the uncertainty of th…
DeepGLEAM: A hybrid mechanistic and deep learning model for COVID-19 forecasting
Dongxia Wu, Liyao Gao, Xinyue Xiong +4
We introduce DeepGLEAM, a hybrid model for COVID-19 forecasting. DeepGLEAM combines a mechanistic stochastic simulation model GLEAM with deep learning. It uses deep learning to lea…
Predicting seasonal influenza using supermarket retail records
Ioanna Miliou, Xinyue Xiong, Salvatore Rinzivillo +5
Increased availability of epidemiological data, novel digital data streams, and the rise of powerful machine learning approaches have generated a surge of research activity on real…
Inferring high-resolution human mixing patterns for disease modeling
Dina Mistry, Maria Litvinova, Ana Pastore y Piontti +12
Mathematical and computational modeling approaches are increasingly used as quantitative tools in the analysis and forecasting of infectious disease epidemics. The growing need for…
Epidemic spreading on time-varying multiplex networks
Quan-Hui Liu, Xinyue Xiong, Qian Zhang +1
Social interactions are stratified in multiple contexts and are subject to complex temporal dynamics. The systematic study of these two features of social systems has started only…