Long-Time Trajectory Approximation via SA-NODEs: Model Predictive and Floquet Strategies
We study the approximation of dynamical systems by semi-autonomous neural ordinary differential equations (SA-NODEs) over long time horizons. For a single network trained on the whole horizon, the available error bound deteriorates double exponentially in the horizon length. We develop two training strategies that avoi...