Physics-Informed Gaussian Process with applications in ODE/PDE parameter estimation
<p>Parameter estimation for nonlinear dynamic system models, represented by ordinary differential equations (ODEs) or partial differential equations (PDEs), using noisy and sparse experimental data is a vital task in many fields. We propose a fast and accurate method, physics-informed Gaussian process, for this task. O...