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cs.LG2026
Structure-Preserving Gaussian Processes Via Discrete Euler-Lagrange Equations
Jan-Hendrik Ewering, Kathrin Flaßkamp, Niklas Wahlström +2
In this paper, we propose Lagrangian Gaussian Processes (LGPs) for probabilistic and data-efficient learning of dynamics via discrete forced Euler-Lagrange equations. Importantly,…
cs.LG2023★ 9 cited
Hamiltonian Neural Networks with Automatic Symmetry Detection
Eva Dierkes, Christian Offen, Sina Ober-Blöbaum +1
Recently, Hamiltonian neural networks (HNN) have been introduced to incorporate prior physical knowledge when learning the dynamical equations of Hamiltonian systems. Hereby, the s…