标签
The paper presents a controlled matched-integrator evaluation of Hamiltonian Neural Networks against a parameter-matched baseline on pendulum and Kepler dynamics, showing significant reductions in energy drift and trajectory error. It also examines the behavior of Störmer–Verlet-style rollouts with learned non-separable Hamiltonians.