Before revision:  In particular, we introduce a neural-network control (NNC) framework, which represents dynamical systems by neural ordinary different equations (neural ODEs) , and find that NNC can learn control signals that drive networked dynamical systems into desired target states.
After revision:  In particular, we introduce a neural-network control (NNC) framework, which represents dynamical systems by neural ordinary different equations (neural ODEs) , and find that NNC can learn control signals that drive graph dynamical systems into desired target states.