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SEINN: A deep learning algorithm for the stochastic epidemic model
Thomas Torku
, Abdul Khaliq
,
Fathalla Rihan
Department of Mathematical Sciences
Research output
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Contribution to journal
›
Article
›
peer-review
7
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Keyphrases
Analysis Center
25%
Comprehensive Representation
25%
Computational Analysis
25%
Data Parameters
25%
Data Systems
25%
Deep Learning Algorithm
100%
Deep Neural Network
25%
Deterministic Model
50%
Dynamical Systems
25%
Epidemic Model
25%
Epidemiology
25%
Error Metrics
25%
Mitigation Policy
25%
Neural Network
25%
Nonlinear Incidence
100%
Overfitting
25%
Parameter System
25%
Politicians
25%
Sensitivity Analysis
25%
Stochastic Epidemic
25%
Stochastic Epidemic Model
100%
Stochastic Model
50%
Stochastic Modeling
25%
Stochasticity
75%
Tennessee
25%
Use Error
25%
Vaccination
25%
Vaccination Policy
25%
Vaccination Rate
25%
Vaccine Model
25%
Mathematics
Combined Effect
25%
Computational Analysis
25%
Deep Learning Method
100%
Deep Neural Network
25%
Deterministic Model
50%
Dynamical System
25%
Empirical evidence
25%
Incidence Rate
100%
Neural Network
25%
Stochastic Model
50%
Stochastics
100%
Computer Science
Case Study
25%
Combined Effect
25%
Deep Learning Method
100%
Deep Neural Network
25%
Deterministic Model
50%
Dynamical System
25%
Empirical evidence
25%
Incidence Rate
100%
Neural Network
25%
Stochastic Model
50%
United States of America
25%