HiLNN conditions Lagrangian dynamics on a latent context encoded from position history, enabling position-only long-horizon forecasting that outperforms LNN/HNN/Neural ODE baselines on three pendulum settings.
In: ICLR 2020 Workshop on Integration of Deep Neural Models and Differential Equations (2020)
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History-informed Lagrangian Neural Networks
HiLNN conditions Lagrangian dynamics on a latent context encoded from position history, enabling position-only long-horizon forecasting that outperforms LNN/HNN/Neural ODE baselines on three pendulum settings.