- Publication Date:
- NSF-PAR ID:
- Journal Name:
- 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
- Volume 1: KDIR
- Page Range or eLocation-ID:
- Sponsoring Org:
- National Science Foundation
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Materials and Methods
We proposed a spatio-temporal attention network (STAN) for pandemic prediction. It uses a graph attention network to capture spatio-temporal trends of disease dynamics and to predict the number of cases for a fixed number of daysmore »
STAN outperforms traditional epidemiological models such as susceptible-infectious-recovered (SIR), susceptible-exposed-infectious-recovered (SEIR), and deep learning models on both long-term and short-term predictions, achieving up to 87% reduction in mean squared error compared to the best baseline prediction model.
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