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Going by the numbers: Learning and modeling COVID-19 disease dynamics
Sayantani Basu,
Roy H. Campbell
Siebel School of Computing and Data Science
Information Trust Institute
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Keyphrases
Infection Rate
100%
Mitigation Measures
100%
Disease Dynamics
100%
Number Learning
100%
COVID-19 Disease
100%
Modelling COVID-19
100%
United States
50%
Disinfection
50%
Valuable Insight
50%
Death Rate
50%
State-based
50%
Memory-based Model
50%
Societal Benefits
50%
Mitigation Strategies
50%
County Level
50%
Global Concern
50%
Countries Worldwide
50%
Number of Deaths
50%
Long Short-term Memory
50%
Window Parameters
50%
Long Short-term Memory Model
50%
COVID-19
50%
Social Distancing
50%
COVID-19 Pandemic
50%
Lockdown
50%
COVID-19 Cases
50%
Coronavirus Disease (COVID)
50%
Reopening Strategies
50%
COVID-19 Mortality
50%
Disease COVID-19
50%
Computer Science
Long Short-Term Memory Network
100%
Quantitative Comparison
50%
Memory Model
50%
Neuroscience
Short-Term Memory
100%
Coronavirinae
50%
SARS Coronavirus
50%
Chemical Engineering
Long Short-Term Memory
100%
Mathematics
Disease Dynamic
100%