417 citations · 420 across the 5 of their papers we have counts for
6 papers
Are Statistical Methods Obsolete in the Era of Deep Learning? A Study of ODE Inverse Problems
Skyler Wu, Shihao Yang, S. C. Kou
In the era of AI, neural networks have become increasingly popular for modeling, inference, and prediction, largely due to their potential for universal approximation. With the pro…
Estimating and Assessing Differential Equation Models with Time-Course Data
Samuel W. K. Wong, Shihao Yang, S. C. Kou
Ordinary differential equation (ODE) models are widely used to describe chemical or biological processes. This article considers the estimation and assessment of such models on the…
MAGI: A Package for Inference of Dynamic Systems from Noisy and Sparse Data via Manifold-constrained Gaussian Processes
Samuel W. K. Wong, Shihao Yang, S. C. Kou
This article presents the MAGI software package for the inference of dynamic systems. The focus of MAGI is on dynamics modeled by nonlinear ordinary differential equations with unk…
Inference of dynamic systems from noisy and sparse data via manifold-constrained Gaussian processes
Shihao Yang, Samuel W. K. Wong, S. C. Kou
Parameter estimation for nonlinear dynamic system models, represented by ordinary differential equations (ODEs), using noisy and sparse data is a vital task in many fields. We prop…
Use Internet Search Data to Accurately Track State-Level Influenza Epidemics
Shihao Yang, Shaoyang Ning, S. C. Kou
For epidemics control and prevention, timely insights of potential hot spots are invaluable. Alternative to traditional epidemic surveillance, which often lags behind real time by…
Accurate estimation of influenza epidemics using Google search data via ARGO
Shihao Yang, Mauricio Santillana, S. C. Kou
Accurate real-time tracking of influenza outbreaks helps public health officials make timely and meaningful decisions that could save lives. We propose an influenza tracking model,…