Offen, Christian, and Sina Ober-Blöbaum. “Learning of Discrete Models of Variational PDEs from Data.”10.1063/5.0172287__Chaos, vol. 34, no. 1, 013104, AIP Publishing, 2024, doi:10.1063/5.0172287.
LibreCat: /record/46469
DOI: 10.1063/5.0172287
arXiv: 2308.05082 

Leyendecker, Sigrid, et al. “A New Lagrangian Approach to Control Affine Systems with a Quadratic Lagrange Term.”10.3934/jcd.2024017__Journal of Computational Dynamics, vol. 0, no. 0, American Institute of Mathematical Sciences (AIMS), 2024, pp. 0–0, doi:10.3934/jcd.2024017.
LibreCat: /record/53101
DOI: 10.3934/jcd.2024017

Offen, Christian, and Sina Ober-Blöbaum. “Learning Discrete Lagrangians for Variational PDEs from Data and Detection of Travelling Waves.”10.1007/978-3-031-38271-0_57__Geometric Science of Information, edited by F Nielsen and F Barbaresco, vol. 14071, Springer, Cham., 2023, pp. 569–79, doi:10.1007/978-3-031-38271-0_57.
LibreCat: /record/42163
DOI: 10.1007/978-3-031-38271-0_57
arXiv: 2302.08232 

Ober-Blöbaum, Sina, and Christian Offen. “Variational Learning of Euler–Lagrange Dynamics from Data.”10.1016/j.cam.2022.114780__Journal of Computational and Applied Mathematics, vol. 421, Elsevier, 2023, p. 114780, doi:10.1016/j.cam.2022.114780.
LibreCat: /record/29240
DOI: 10.1016/j.cam.2022.114780
arXiv: 2112.12619

Dierkes, Eva, et al. “Hamiltonian Neural Networks with Automatic Symmetry Detection.”10.1063/5.0142969__Chaos, vol. 33, no. 6, 063115, AIP Publishing, 2023, doi:10.1063/5.0142969.
LibreCat: /record/37654
DOI: 10.1063/5.0142969
arXiv: 2301.07928

Dellnitz, Michael, et al. “Efficient Time Stepping for Numerical Integration Using Reinforcement  Learning.”10.1137/21M1412682__SIAM Journal on Scientific Computing, vol. 45, no. 2, 2023, pp. 9–95, doi:10.1137/21M1412682.
LibreCat: /record/21600
DOI: 10.1137/21M1412682
arXiv: arXiv:2104.03562

Lishkova, Yana, et al. Multirate Discrete Mechanics and Optimal Control for a Flexible Satelite Model . Invited Mathematical Magazine Article, 2023.
LibreCat: /record/47147

Lishkova, Y., et al. Variational Approach for Modelling and Optimal Control of Electrodynamic Tether Motion. Accepted for the 74th International Astronautical Concress (IAC), 2023.
LibreCat: /record/47148

Lishkova, Yana, et al. “Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery.”10.1016/j.ifacol.2023.10.1457__IFAC-PapersOnLine, vol. 56, no. 2, Elsevier, 2023, pp. 3203–10, doi:10.1016/j.ifacol.2023.10.1457.
LibreCat: /record/34135
DOI: 10.1016/j.ifacol.2023.10.1457
arXiv: 2211.10830

Cresson, Jacky, et al. “Continuous and Discrete Noether’s Fractional Conserved Quantities for Restricted Calculus of Variations.” AIMS, vol. 14(1), 2022, pp. 57–89.
LibreCat: /record/30490

Faulwasser, Timm, et al. “Manifold Turnpikes, Trims, and Symmetries.” Mathematics of Control, Signals, and Systems, vol. 34, Springer, 2022, pp. 759–88.
LibreCat: /record/44624

Offen, Christian, and Sina Ober-Blöbaum. “Symplectic Integration of Learned Hamiltonian Systems.”10.1063/5.0065913__Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 32(1), AIP, 2022, doi:10.1063/5.0065913.
LibreCat: /record/23382
DOI: 10.1063/5.0065913
arXiv: 2108.02492

Vertovec, Nikolaus, et al. Verification of Safety Critical Control Policies Using Kernel Methods. 2022, pp. 1870–75.
LibreCat: /record/30733

Ober-Blöbaum, Sina, and M. Vermeeren. “Superconvergence of Galerkin Variational Integrators.” 7th IIFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control LHMNC, edited by IFAC-PapersOnLine, vol. 54(19), 2021, pp. 327–33.
LibreCat: /record/29421

Ober-Blöbaum, Sina, and Sebastian Peitz. “Explicit Multiobjective Model Predictive Control for Nonlinear Systems  with Symmetries.”10.1002/rnc.5281__International Journal of Robust and Nonlinear Control, vol. 31(2), 2021, pp. 380–403, doi:10.1002/rnc.5281.
LibreCat: /record/16294
DOI: 10.1002/rnc.5281

Lishkova, Y., et al. A Multirate Variational Approach to Nonlinear MPC. European Control Conference (ECC), IEEE, 2021.
LibreCat: /record/47146

Offen, Christian, and Sina Ober-Blöbaum. Bifurcation Preserving Discretisations of Optimal Control Problems. 2021, pp. 334–39, doi:https://doi.org/10.1016/j.ifacol.2021.11.099.
LibreCat: /record/22894
DOI: https://doi.org/10.1016/j.ifacol.2021.11.099
arXiv: 2107.13853

Ridderbusch, Steffen, et al. “Learning ODE Models with Qualitative Structure Using Gaussian Processes .”10.1109/CDC45484.2021.9683426__2021 60th IEEE Conference on Decision and Control (CDC), IEEE, 2021, p. 2896, doi:10.1109/CDC45484.2021.9683426.
LibreCat: /record/21572
DOI: 10.1109/CDC45484.2021.9683426
arXiv: 2011.05364

Vertovec, Nikolaus, et al. Multi-Objective Minimum Time Optimal Control for Low-Thrust Trajectory Design. pp. 1975–80.
LibreCat: /record/21592
arXiv: 2103.08813

Jiménez, F., and Sina Ober-Blöbaum. “Fractional Damping Through Restricted Calculus of Variations.” Nichtlineare Sci 31, vol. 46, 2021.
LibreCat: /record/29868