82 citations · 118 across the 15 of their papers we have counts for
7 papers · 1 filter
Modeling Epidemic Spread: A Gaussian Process Regression Approach
Baike She, Lei Xin, Philip E. Paré +1
Modeling epidemic spread is critical for informing policy decisions aimed at mitigation. Accordingly, in this work we present a new data-driven method based on Gaussian process reg…
Reverse Engineering the Reproduction Number: A Framework for Data-Driven Counterfactual Analysis, Strategy Evaluation, and Feedback Control of Epidemics
Baike She, Rebecca Lee Smith, Ian Pytlarz +2
During the COVID-19 pandemic, different countries, regions, and communities constructed various epidemic models to evaluate spreading behaviors and assist in making mitigation poli…
Differentially Private Computation of Basic Reproduction Numbers in Networked Epidemic Models
Bo Chen, Baike She, Calvin Hawkins +4
The basic reproduction number of a networked epidemic model, denoted , can be computed from a network's topology to quantify epidemic spread. However, disclosure of risk…
Characterizing Compositionality of LQR from the Categorical Perspective
Baike She, Tyler Hanks, James Fairbanks +1
Composing systems is a fundamental concept in modern control systems, yet it remains challenging to formally analyze how controllers designed for individual subsystems can differ f…
Modeling Model Predictive Control: A Category Theoretic Framework for Multistage Control Problems
Tyler Hanks, Baike She, Matthew Hale +3
Model predictive control (MPC) is an optimal control technique which involves solving a sequence of constrained optimization problems across a given time horizon. In this paper, we…
Leveraging Opinions and Vaccination to Eradicate Networked Epidemics
Humphrey Leung, Zhuocong Li, Baike She +1
We introduce a multi-layer networked compartmental model that captures opinion dynamics, disease spread, risk perception, and self-interest vaccine-uptake behavior in an…
Distributed Reproduction Numbers of Networked Epidemics
Baike She, Philip E. Paré, Matthew Hale
Reproduction numbers are widely used for the estimation and prediction of epidemic spreading processes over networks. However, reproduction numbers do not enable estimation and pre…