Learning of discrete models of variational PDEs from data
C. Offen, S. Ober-Blöbaum, Chaos 34 (2024).

A new Lagrangian approach to control affine systems with a quadratic Lagrange term
S. Leyendecker, S. Maslovskaya, S. Ober-Blöbaum, R.T.S.M. de Almagro, F.O. Szemenyei, Journal of Computational Dynamics 0 (2024) 0–0.

Machine learning of continuous and discrete variational ODEs with convergence guarantee and uncertainty quantification
C. Offen, (n.d.).

Learning discrete Lagrangians for variational PDEs from data and detection of travelling waves
C. Offen, S. Ober-Blöbaum, in: F. Nielsen, F. Barbaresco (Eds.), Geometric Science of Information, Springer, Cham., 2023, pp. 569–579.

Variational Learning of Euler–Lagrange Dynamics from Data
S. Ober-Blöbaum, C. Offen, Journal of Computational and Applied Mathematics 421 (2023) 114780.

Backward error analysis for conjugate symplectic methods
R. McLachlan, C. Offen, Journal of Geometric Mechanics 15 (2023) 98–115.

Hamiltonian Neural Networks with Automatic Symmetry Detection
E. Dierkes, C. Offen, S. Ober-Blöbaum, K. Flaßkamp, Chaos 33 (2023).

Efficient time stepping for numerical integration using reinforcement  learning
M. Dellnitz, E. Hüllermeier, M. Lücke, S. Ober-Blöbaum, C. Offen, S. Peitz, K. Pfannschmidt, SIAM Journal on Scientific Computing 45 (2023) 9–5.

Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery
Y. Lishkova, P. Scherer, S. Ridderbusch, M. Jamnik, P. Liò, S. Ober-Blöbaum, C. Offen, in: IFAC-PapersOnLine, Elsevier, 2023, pp. 3203–3210.

Continuous and discrete Noether's fractional conserved quantities for restricted calculus of variations
J. Cresson, F. Jiménez, S. Ober-Blöbaum, AIMS 14(1) (2022) 57–89.