We construct generalized Lyapunov certificates by augmenting value functions with residual terms to certify the stability of control policies from optimal control or reinforcement learning.

The present work proposes stable port-Hamiltonian neural networks for accurate, robust, and reliable identification of stable nonlinear dynamic systems.