Author: swarna kamal paul; Saikat Jana; Parama Bhaumik
Title: A multivariate spatiotemporal spread model of COVID-19 using ensemble of ConvLSTM networks Document date: 2020_4_22
ID: nng76upj_25
Snippet: An ensemble of Convolutional LSTM based spatiotemporal epidemic spread model has been proposed for short term forecasting of Covid-19 spread. Experiments done on data obtained for USA and Italy reveals high prediction accuracy with high resolution. Since the model has option to fed in any number of external features so we are experimenting with multiple external features that might influence the spread. This might help to find important causal fe.....
Document: An ensemble of Convolutional LSTM based spatiotemporal epidemic spread model has been proposed for short term forecasting of Covid-19 spread. Experiments done on data obtained for USA and Italy reveals high prediction accuracy with high resolution. Since the model has option to fed in any number of external features so we are experimenting with multiple external features that might influence the spread. This might help to find important causal features that are impacting the spread across multiple locations. We are also trying to combine models of multiple countries so that a single ensemble of model can be trained through transfer learning and will eventually help predicting cases across the globe.
Search related documents:
Co phrase search for related documents- epidemic spread and high resolution: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
- epidemic spread and multiple country: 1, 2, 3
- epidemic spread model and high resolution: 1, 2, 3
- high prediction accuracy and model single ensemble: 1
Co phrase search for related documents, hyperlinks ordered by date