Trim turnpikes for optimal control problems with symmetries
K. Flaßkamp, S. Maslovskaya, S. Ober-Blöbaum, B.E. Wembe Moafo, Mathematics of Control, Signals, and Systems (2025).

On the variational discretization of optimal control problems for Lagrangian dynamics
M. Konopik, S. Leyendecker, S. Maslovskaya, S. Ober-Blöbaum, R.T.S.M. de Almagro, (2025).

Variational integrators for a new Lagrangian approach to control affine systems with a quadratic Lagrange term
M. Konopik, R. T. Sato Martín de Almagro, S. Maslovskaya, S. Ober-Blöbaum, S. Leyendecker, (2025).

A new Lagrangian approach to optimal control of second-order systems
M. Konopik, S. Leyendecker, S. Maslovskaya, S. Ober-Blöbaum, R. T. Sato Martín de Almagro, (2025).

Multiphoton, multimode state classification for nonlinear optical circuits 
D. Kopylov, C. Offen, L. Ares, B.E. Wembe Moafo, S. Ober-Blöbaum, T. Meier, P. Sharapova, J. Sperling, (n.d.).

Machine learning of continuous and discrete variational ODEs with convergence guarantee and uncertainty quantification
C. Offen, Mathematics of Computation (2025).

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.

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

Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification
C. Offen, (n.d.).

Symplectic Methods in Deep Learning
S. Maslovskaya, S. Ober-Blöbaum, in: IFAC-PapersOnLine, Elsevier BV, 2024, pp. 85–90.

Adaptive higher order reversible integrators for memory efficient deep learning
S. Maslovskaya, S. Ober-Blöbaum, C. Offen, P. Singh, B.E. Wembe Moafo, (2024).

Inverse optimal control problem in the non autonomous linear-quadratic case
F. Jean, S. Maslovskaya, (2024).

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.

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.

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.

Turnpike Property in Optimal Microbial Metabolite Production
J.-B. Caillau, W. Djema, J.-L. Gouzé, S. Maslovskaya, J.-B. Pomet, Journal of Optimization Theory and Applications (2022).