A structure-preserving neural network method identifies nonlinear port-Hamiltonian systems from input-state-output data, improving long-term forecasting over physics-free baselines.
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Nonlinear port-Hamiltonian system identification from input-state-output data
A structure-preserving neural network method identifies nonlinear port-Hamiltonian systems from input-state-output data, improving long-term forecasting over physics-free baselines.