Learning Schwarzschild Geodesic Motion with Lagrangian Neural Networks
Lagrangian Neural Networks (LNNs) learn dynamics from trajectory data by parameterizing a scalar Lagrangian and deriving accelerations through the Euler--Lagrange equation, providing a variational inductive bias that improves physical consistency over purely data-driven models. LNNs have recently been extended to gener...
Sukru Caglar, S. Kalabalik, Abdullah Umut Hamzaogullari et al.
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