Offen, C., &; Ober-Blöbaum, S. (2024). Learning of discrete models of variational PDEs from data. Chaos, 34(1), Article 013104.https://doi.org/10.1063/5.0172287 

Gebken, B. (2024). A note on the convergence of deterministic gradient sampling in nonsmooth optimization. Computational Optimization and Applications.https://doi.org/10.1007/s10589-024-00552-0 

Sonntag, K., &; Peitz, S. (2024). Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems. Journal of Optimization Theory and Applications.https://doi.org/10.1007/s10957-024-02389-3 

Sonntag, K., Gebken, B., Müller, G., Peitz, S., &; Volkwein, S. (2024). A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces. In arXiv:2402.06376.

Dalfó, C., Fiol, M. A., &; Steffen, E. (2024). On token signed graphs. In arXiv:2403.02924.

Bick, C., &; von der Gracht, S. (2024). Heteroclinic dynamics in network dynamical systems with higher-order interactions. Journal of Complex Networks, 12(2).https://doi.org/10.1093/comnet/cnae009 

Ma, Y., Mattiolo, D., Steffen, E., &; Wolf, I. H. (2024). Edge-Connectivity and Pairwise Disjoint Perfect Matchings in Regular Graphs. Combinatorica, 44, 429–440.https://doi.org/10.1007/s00493-023-00078-9 

Leyendecker, S., Maslovskaya, S., Ober-Blöbaum, S., Almagro, R. T. S. M. de, &; Szemenyei, F. O. (2024). A new Lagrangian approach to control affine systems with a quadratic Lagrange term. Journal of Computational Dynamics, 0(0), 0–0.https://doi.org/10.3934/jcd.2024017 

Edelmann, D., Kovács, B., &; Lubich, C. (2024). Numerical analysis of an evolving bulk--surface model of tumour growth. ArXiv.https://doi.org/10.48550/ARXIV.2401.09372 

Kovács, B. (2024). Numerical surgery for mean curvature flow of surfaces. SIAM Journal on Scientific Computing, 46(2).https://doi.org/10.1137/22M1531919 

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

Ernst, A., &; Schmidt, K.-U. (2024). Transitivity in finite general linear groups. Mathematische Zeitschrift, 307(45).https://doi.org/10.1007/s00209-024-03511-x 

Peitz, S., &; Bieker, K. (2023). On the Universal Transformation of Data-Driven Models to Control Systems. Automatica, 149, Article 110840.https://doi.org/10.1016/j.automatica.2022.110840 

Gebken, B., Bieker, K., &; Peitz, S. (2023). On the structure of regularization paths for piecewise differentiable regularization terms. Journal of Global Optimization, 85(3), 709–741.https://doi.org/10.1007/s10898-022-01223-2 

Cappello, C., Naserasr, R., Steffen, E., &; Wang, Z. (2023). Critically 3-frustrated signed graphs. In arXiv:2304.10243.

Silva, H. O. M., Rubert, D. P., Araujo, E., Steffen, E., Doerr, D., &; Martinez, F. V. (2023). Algorithms for the genome median under a restricted measure of rearrangement. RAIRO - Operations Research, 57(3), 1045–1058.https://doi.org/10.1051/ro/2023052 

Ma, Y., Mattiolo, D., Steffen, E., &; Wolf, I. H. (2023). Sets of r-graphs that color all r-graphs. In arXiv:2305.08619.

von der Gracht, S., Nijholt, E., &; Rink, B. (n.d.). A parametrisation method for high-order phase reduction in coupled  oscillator networks. In arXiv:2306.03320.

Ma, Y., Mattiolo, D., Steffen, E., &; Wolf, I. H. (2023). Pairwise Disjoint Perfect Matchings in r-Edge-Connected r-Regular Graphs. SIAM Journal on Discrete Mathematics, 37(3), 1548–1565.https://doi.org/10.1137/22m1500654 

Offen, C., &; Ober-Blöbaum, S. (2023). Learning discrete Lagrangians for variational PDEs from data and detection of travelling waves. In F. Nielsen &; F. Barbaresco (Eds.), Geometric Science of Information (Vol. 14071, pp. 569–579). Springer, Cham.https://doi.org/10.1007/978-3-031-38271-0_57