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Modeling and Predicting Epidemic Spread: A Gaussian Process Regression Approach
Gaussian Process Regression excels in using small datasets and providing uncertainty bounds, and both of these properties are critical in modeling and predicting epidemic spreading processes with limited data.
Characterizing Compositionality of LQR from the Categorical Perspective
Then we develop new sufficient conditions to guarantee that the LQR designed for a composite system is equal to the LQR attained through composition of LQRs for its subsystems.
Distributed Reproduction Numbers of Networked Epidemics
These conditions are then used to derive new conditions for the existence, uniqueness, and stability of equilibrium states.
Optimal Mitigation of SIR Epidemics Under Model Uncertainty
Distinct from existing works on leveraging control strategies in epidemic spreading, we propose a testing strategy by overestimating the seriousness of the epidemic and study the feasibility of the system under the impact of model parameter uncertainty.
Peak Infection Time for a Networked SIR Epidemic with Opinion Dynamics
We propose an SIR epidemic model coupled with opinion dynamics to study an epidemic and opinions spreading in a network of communities.
On a Network SIS Epidemic Model with Cooperative and Antagonistic Opinion Dynamics
We propose a mathematical model to study coupled epidemic and opinion dynamics in a network of communities.
