1 code implementation • 25 May 2021 • Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Deep learning is gaining increasing popularity for spatiotemporal forecasting.
no code implementations • 12 Feb 2021 • Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
We introduce DeepGLEAM, a hybrid model for COVID-19 forecasting.
1 code implementation • 8 Dec 2020 • Ioanna Miliou, Xinyue Xiong, Salvatore Rinzivillo, Qian Zhang, Giulio Rossetti, Fosca Giannotti, Dino Pedreschi, Alessandro Vespignani
In this paper, we propose the use of a novel data source, namely retail market data to improve seasonal influenza forecasting.
1 code implementation • 25 Feb 2020 • Dina Mistry, Maria Litvinova, Ana Pastore y Piontti, Matteo Chinazzi, Laura Fumanelli, Marcelo F. C. Gomes, Syed A. Haque, Quan-Hui Liu, Kunpeng Mu, Xinyue Xiong, M. Elizabeth Halloran, Ira M. Longini Jr., Stefano Merler, Marco Ajelli, Alessandro Vespignani
Mathematical and computational modeling approaches are increasingly used as quantitative tools in the analysis and forecasting of infectious disease epidemics.
Populations and Evolution Physics and Society Quantitative Methods