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Preprint Aug 2026

History-informed Lagrangian Neural Networks

Grounded in the insight that temporal position sequences implicitly encode underlying dynamics, HiLNN employs a recurrent encoder to extract a latent context from history that not only reconstructs the unobserved initial velocity but also adaptively modulates the mass matrix, potential energy, and damping coefficients...

Tian-Shuo Zhang, Xianglei Xing, Wen-Zhe Zhai et al. · 1 citation

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