A discrete forced Lagrangian neural network learns conservative and dissipative dynamics from position data alone and produces structure-preserving rollouts.
Data-driven modeling: concept, techniques, challenges and a case study
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Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics
A discrete forced Lagrangian neural network learns conservative and dissipative dynamics from position data alone and produces structure-preserving rollouts.