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Found 4 papers, 0 papers with code
Estimating the Distribution of Parameters in Differential Equations with Repeated Cross-Sectional Data
With RCS data, we found that traditional methods for parameter estimation in differential equations, such as using mean values of time trajectories or Gaussian Process-based trajectory generation, have limitations in estimating the shape of parameter distributions, often leading to a significant loss of data information.
Machine Learning-Based COVID-19 Patients Triage Algorithm using Patient-Generated Health Data from Nationwide Multicenter Database
The prompt severity assessment model for managing infectious people has been attained through using a nationwide dataset.
Trend to Equilibrium for the Kinetic Fokker-Planck Equation via the Neural Network Approach
The issue of the relaxation to equilibrium has been at the core of the kinetic theory of rarefied gas dynamics.
Deep Neural Network Approach to Forward-Inverse Problems
That is, we provide a unified framework of DNN architecture that approximates an analytic solution and its model parameters simultaneously.
