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math.NA2023★ 4 cited
Learning of discrete models of variational PDEs from data
Christian Offen, Sina Ober-Blöbaum
We show how to learn discrete field theories from observational data of fields on a space-time lattice. For this, we train a neural network model of a discrete Lagrangian density s…
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…