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Found 4 papers, 1 papers with code
Estimating and Assessing Differential Equation Models with Time-Course Data
Overall, we believe MAGI is a useful method for the analysis of time-course data in the context of ODE models, which bypasses the need for any numerical integration.
Inference of dynamic systems from noisy and sparse data via manifold-constrained Gaussian processes
MAGI uses a Gaussian process model over time-series data, explicitly conditioned on the manifold constraint that derivatives of the Gaussian process must satisfy the ODE system.
Methodology Dynamical Systems
Use Internet Search Data to Accurately Track State-Level Influenza Epidemics
ARGOX combines Internet search data at the national, regional and state levels with traditional influenza surveillance data from the Centers for Disease Control and Prevention, and accounts for both the spatial correlation structure of state-level influenza activities and the evolution of people's Internet search pattern.
Applications
Accurate estimation of influenza epidemics using Google search data via ARGO
Accurate real-time tracking of influenza outbreaks helps public health officials make timely and meaningful decisions that could save lives.
