C. Offen and S. Ober-Blöbaum, “Learning of discrete models of variational PDEs from data,”10.1063/5.0172287__Chaos, vol. 34, no. 1, Art. no. 013104, 2024, doi:10.1063/5.0172287 .

B. Gebken, “A note on the convergence of deterministic gradient sampling in nonsmooth optimization,”10.1007/s10589-024-00552-0__Computational Optimization and Applications, 2024, doi:10.1007/s10589-024-00552-0 .

K. Sonntag and S. Peitz, “Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems,”10.1007/s10957-024-02389-3__Journal of Optimization Theory and Applications, 2024, doi:10.1007/s10957-024-02389-3 .

K. Sonntag, B. Gebken, G. Müller, S. Peitz, and S. Volkwein, “A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces,” arXiv:2402.06376. 2024.

C. Dalfó, M. A. Fiol, and E. Steffen, “On token signed graphs,” arXiv:2403.02924. 2024.

C. Bick and S. von der Gracht, “Heteroclinic dynamics in network dynamical systems with higher-order interactions,”10.1093/comnet/cnae009__Journal of Complex Networks, vol. 12, no. 2, 2024, doi:10.1093/comnet/cnae009 .

Y. Ma, D. Mattiolo, E. Steffen, and I. H. Wolf, “Edge-Connectivity and Pairwise Disjoint Perfect Matchings in Regular Graphs,”10.1007/s00493-023-00078-9__Combinatorica, vol. 44, pp. 429–440, 2024, doi:10.1007/s00493-023-00078-9 .

S. Leyendecker, S. Maslovskaya, S. Ober-Blöbaum, R. T. S. M. de Almagro, and F. O. Szemenyei, “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, pp. 0–0, 2024, doi:10.3934/jcd.2024017 .

D. Edelmann, B. Kovács, and C. Lubich, “Numerical analysis of an evolving bulk--surface model of tumour growth,”10.48550/ARXIV.2401.09372__arXiv, 2024, doi:10.48550/ARXIV.2401.09372 .

B. Kovács, “Numerical surgery for mean curvature flow of surfaces,”10.1137/22M1531919__SIAM Journal on Scientific Computing, vol. 46, no. 2, 2024, doi:10.1137/22M1531919 .

C. Offen, “Machine learning of continuous and discrete variational ODEs with convergence guarantee and uncertainty quantification.” .

S. Peitz and K. Bieker, “On the Universal Transformation of Data-Driven Models to Control Systems,”10.1016/j.automatica.2022.110840__Automatica, vol. 149, Art. no. 110840, 2023, doi:10.1016/j.automatica.2022.110840 .

B. Gebken, K. Bieker, and S. Peitz, “On the structure of regularization paths for piecewise differentiable regularization terms,”10.1007/s10898-022-01223-2__Journal of Global Optimization, vol. 85, no. 3, pp. 709–741, 2023, doi:10.1007/s10898-022-01223-2 .

C. Cappello, R. Naserasr, E. Steffen, and Z. Wang, “Critically 3-frustrated signed graphs,” arXiv:2304.10243. 2023.

H. O. M. Silva, D. P. Rubert, E. Araujo, E. Steffen, D. Doerr, and F. V. Martinez, “Algorithms for the genome median under a restricted measure of rearrangement,”10.1051/ro/2023052__RAIRO - Operations Research, vol. 57, no. 3, pp. 1045–1058, 2023, doi:10.1051/ro/2023052 .

Y. Ma, D. Mattiolo, E. Steffen, and I. H. Wolf, “Sets of r-graphs that color all r-graphs,” arXiv:2305.08619. 2023.

S. von der Gracht, E. Nijholt, and B. Rink, “A parametrisation method for high-order phase reduction in coupled  oscillator networks,” arXiv:2306.03320. .

Y. Ma, D. Mattiolo, E. Steffen, and I. H. Wolf, “Pairwise Disjoint Perfect Matchings in r-Edge-Connected r-Regular Graphs,”10.1137/22m1500654__SIAM Journal on Discrete Mathematics, vol. 37, no. 3, pp. 1548–1565, 2023, doi:10.1137/22m1500654 .

C. Offen and S. Ober-Blöbaum, “Learning discrete Lagrangians for variational PDEs from data and detection of travelling waves,”10.1007/978-3-031-38271-0_57__in Geometric Science of Information, Saint-Malo, Palais du Grand Large, France, 2023, vol. 14071, pp. 569–579, doi:10.1007/978-3-031-38271-0_57 .

S. Ober-Blöbaum and C. Offen, “Variational Learning of Euler–Lagrange Dynamics from Data,”10.1016/j.cam.2022.114780__Journal of Computational and Applied Mathematics, vol. 421, p. 114780, 2023, doi:10.1016/j.cam.2022.114780 .

R. McLachlan and C. Offen, “Backward error analysis for conjugate symplectic methods,”10.3934/jgm.2023005__Journal of Geometric Mechanics, vol. 15, no. 1, pp. 98–115, 2023, doi:10.3934/jgm.2023005 .

E. Dierkes, C. Offen, S. Ober-Blöbaum, and K. Flaßkamp, “Hamiltonian Neural Networks with Automatic Symmetry Detection,”10.1063/5.0142969__Chaos, vol. 33, no. 6, Art. no. 063115, 2023, doi:10.1063/5.0142969 .

F. Nüske, S. Peitz, F. Philipp, M. Schaller, and K. Worthmann, “Finite-data error bounds for Koopman-based prediction and control,”10.1007/s00332-022-09862-1__Journal of Nonlinear Science, vol. 33, Art. no. 14, 2023, doi:10.1007/s00332-022-09862-1 .

M. Dellnitz et al., “Efficient time stepping for numerical integration using reinforcement  learning,”10.1137/21M1412682__SIAM Journal on Scientific Computing, vol. 45, no. 2, pp. 9–5, 2023, doi:10.1137/21M1412682 .

S. von der Gracht, E. Nijholt, and B. Rink, “Hypernetworks: Cluster Synchronization Is a Higher-Order Effect,”10.1137/23m1561075__SIAM Journal on Applied Mathematics, vol. 83, no. 6, pp. 2329–2353, 2023, doi:10.1137/23m1561075 .

S. von der Gracht, E. Nijholt, and B. Rink, “Higher order interactions lead to ‘reluctant’ synchrony breaking,” arXiv:2311.17186. 2023.

J. Klüners and J. Wang, “Idélic Approach in Enumerating Heisenberg Extensions,”10.1007/s44007-023-00067-w__La Matematica, 2023, doi:10.1007/s44007-023-00067-w .

Y. Lishkova et al., “Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery,”10.1016/j.ifacol.2023.10.1457__in IFAC-PapersOnLine,10.1016/j.ifacol.2023.10.1457__Yokohama, Japan, 2023, vol. 56, no. 2, pp. 3203–3210, doi:10.1016/j.ifacol.2023.10.1457 .

R. Gerlach, S. von der Gracht, and M. Dellnitz, “On the Dynamical Hierarchy in Gathering Protocols with Circulant  Topologies,” arXiv:2305.06632. .

K.-U. Schmidt and C. Weiß, “Packings and Steiner systems in polar spaces,”10.5070/c63160424__Combinatorial Theory, vol. 3, no. 1, 2023, doi:10.5070/c63160424 .

K. Schmidt and C. Weiß, “Existence of small ordered orthogonal arrays,”10.1002/jcd.21903__Journal of Combinatorial Designs, vol. 31, no. 9, pp. 422–431, 2023, doi:10.1002/jcd.21903 .

C. Weiß, Linear programming bounds in classical association schemes. 2023.

C. Weiß, “Nontrivial $t$-designs in polar spaces exist for all $t$,” arXiv:2311.08288. .

E. Steffen and I. H. Wolf, “Bounds for the chromatic index of signed multigraphs,”10.1016/j.dam.2023.05.008__Discrete Applied Mathematics, vol. 337, pp. 185–189, 2023, doi:10.1016/j.dam.2023.05.008 .

C. Cappello and E. Steffen, “Graph-Theoretical Models for the Analysis and Design of Socio-Technical Networks,” in The Digital Twin of Humans, Cham: Springer International Publishing, 2023, pp. 93--110.

E. Steffen and I. H. Wolf, “Rotation r-graphs,”10.1016/j.disc.2023.113457__Discrete Mathematics, Art. no. 113457, 2023, doi:10.1016/j.disc.2023.113457 .

K. Sonntag and S. Peitz, “Fast Convergence of Inertial Multiobjective Gradient-like Systems with Asymptotic Vanishing Damping,” arXiv:2307.00975. 2023.

M. Bernreuther et al., “Multiobjective Optimization of Non-Smooth PDE-Constrained Problems,” arXiv:2308.01113. 2023.

I. Gräßler, G. W. Maier, E. Steffen, and D. Roesmann, Eds., The Digital Twin of Humans. Cham: Springer International Publishing, 2023.

S. Bartels, B. Kovács, and Z. Wang, “Error analysis for the numerical approximation of the harmonic map heat flow with nodal constraints,”10.1093/imanum/drad037__IMA Journal of Numerical Analysis, 2023, doi:10.1093/imanum/drad037 .

A. Contri, B. Kovács, and A. Massing, “Error analysis of BDF 1-6 time-stepping methods for the transient Stokes problem: velocity and pressure estimates,”10.48550/ARXIV.2312.05511__arXiv, 2023, doi:10.48550/ARXIV.2312.05511 .

A. Ernst and K.-U. Schmidt, “Intersection theorems for finite general linear groups,”10.1017/s0305004123000075__Mathematical Proceedings of the Cambridge Philosophical Society, vol. 175, no. 1, pp. 129–160, 2023, doi:10.1017/s0305004123000075 .

S. Banholzer, B. Gebken, M. Dellnitz, S. Peitz, and S. Volkwein, “ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation,” in Non-Smooth and Complementarity-Based Distributed Parameter Systems, H. Michael, H. Roland, K. Christian, U. Michael, and U. Stefan, Eds. Cham: Springer, 2022, pp. 43–76.

S. Peitz, M. Dellnitz, and S. Bannenberg, “Efficient Virtual Design and Testing of Autonomous Vehicles,” in German Success Stories in Industrial Mathematics, vol. 35, H. G. Bock, K.-H. Küfer, P. Maas, A. Milde, and V. Schulz, Eds. Cham: Springer International Publishing, 2022.

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

J.-B. Caillau, W. Djema, J.-L. Gouzé, S. Maslovskaya, and J.-B. Pomet, “Turnpike Property in Optimal Microbial Metabolite Production,”10.1007/s10957-022-02023-0__Journal of Optimization Theory and Applications, 2022, doi:10.1007/s10957-022-02023-0 .

S. Klus, F. Nüske, and S. Peitz, “Koopman analysis of quantum systems,”10.1088/1751-8121/ac7d22__Journal of Physics A: Mathematical and Theoretical, vol. 55, no. 31, p. 314002, 2022, doi:10.1088/1751-8121/ac7d22 .

B. Gebken, “Using second-order information in gradient sampling methods for  nonsmooth optimization,” arXiv:2210.04579. 2022.

B. Gebken, Computation and analysis of Pareto critical sets in smooth and nonsmooth multiobjective optimization. 2022.

M. B. Berkemeier and S. Peitz, “Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients,” arXiv:2208.12094. 2022.

K. Bieker, B. Gebken, and S. Peitz, “On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation,”10.1109/TPAMI.2021.3114962__IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 11, pp. 7797–7808, 2022, doi:10.1109/TPAMI.2021.3114962 .

M. Kirschmer and J. Klüners, “Chow groups of orders in number fields,” arXiv:2208.14688. 2022.

J. Klüners and J. Wang, “-torsion bounds for the class group of number fields with an -group as Galois group,”10.1090/proc/15882__Proceedings of the American Mathematical Society, vol. 150, no. 7, pp. 2793–2805, 2022, doi:10.1090/proc/15882 .

J. Klüners, “The asymptotics of nilpotent Galois groups,”10.4064/aa211207-16-5__Acta Arithmetica, vol. 204, no. 2, pp. 165–184, 2022, doi:10.4064/aa211207-16-5 .

M. Kirschmer and J. Klüners, “Chow groups of orders in number fields.” 2022.

T. Faulwasser, K. Flaßkamp, S. Ober-Blöbaum, M. Schaller, and K. Worthmann, “Manifold turnpikes, trims, and symmetries,” Mathematics of Control, Signals, and Systems, vol. 34, pp. 759–788, 2022.

C. Cappello and E. Steffen, “Symmetric Set Coloring of Signed Graphs,”10.1007/s00026-022-00593-4__Annals of Combinatorics, 2022, doi:10.1007/s00026-022-00593-4 .

C. Cappello and E. Steffen, “Frustration-critical signed graphs,”10.1016/j.dam.2022.08.010__Discrete Applied Mathematics, vol. 322, pp. 183–193, 2022, doi:10.1016/j.dam.2022.08.010 .

M. Kirschmer and G. Nebe, “Binary Hermitian Lattices over Number Fields,”10.1080/10586458.2019.1618756__Experimental Mathematics, vol. 31, no. 1, pp. 280–301, 2022, doi:10.1080/10586458.2019.1618756 .

R. I. McLachlan and C. Offen, “Backward error analysis for variational discretisations of partial  differential equations,”10.3934/jgm.2022014__Journal of Geometric Mechanics, vol. 14, no. 3, pp. 447–471, 2022, doi:10.3934/jgm.2022014 .

C. Offen and S. Ober-Blöbaum, “Symplectic integration of learned Hamiltonian systems,”10.1063/5.0065913__Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 32(1), 2022, doi:10.1063/5.0065913 .

N. Vertovec, S. Ober-Blöbaum, and K. Margellos, “Verification of safety critical control policies using kernel methods,” London, 2022, pp. 1870–1875.

H. Garcke, B. Kovács, and D. Trautwein, “Viscoelastic Cahn–Hilliard models for tumor growth,”10.1142/s0218202522500634__Mathematical Models and Methods in Applied Sciences, vol. 32, no. 13, pp. 2673–2758, 2022, doi:10.1142/s0218202522500634 .

C. M. Elliott, H. Garcke, and B. Kovács, “Numerical analysis for the interaction of mean curvature flow and diffusion on closed surfaces,”10.1007/s00211-022-01301-3__Numerische Mathematik, vol. 151, no. 4, pp. 873–925, 2022, doi:10.1007/s00211-022-01301-3 .

J. Nick, B. Kovács, and C. Lubich, “Time-dependent electromagnetic scattering from thin layers,”10.1007/s00211-022-01277-0__Numerische Mathematik, vol. 150, no. 4, pp. 1123–1164, 2022, doi:10.1007/s00211-022-01277-0 .

B. Kovács and B. Li, “Maximal regularity of backward difference time discretization for evolving surface PDEs and its application to nonlinear problems,”10.1093/imanum/drac033__IMA Journal of Numerical Analysis, 2022, doi:10.1093/imanum/drac033 .

R. Altmann, B. Kovács, and C. Zimmer, “Bulk–surface Lie splitting for parabolic problems with dynamic boundary conditions,”10.1093/imanum/drac002__IMA Journal of Numerical Analysis, vol. 43, no. 2, pp. 950–975, 2022, doi:10.1093/imanum/drac002 .

P. Csomós, B. Farkas, and B. Kovács, “Error estimates for a splitting integrator for abstract semilinear boundary coupled systems,”10.1093/imanum/drac079__IMA Journal of Numerical Analysis, 2022, doi:10.1093/imanum/drac079 .

C. A. Beschle and B. Kovács, “Stability and error estimates for non-linear Cahn–Hilliard-type equations on evolving surfaces,”10.1007/s00211-022-01280-5__Numerische Mathematik, vol. 151, no. 1, pp. 1–48, 2022, doi:10.1007/s00211-022-01280-5 .

J. Bohn, M. Feischl, and B. Kovács, “FEM-BEM Coupling for the Maxwell–Landau–Lifshitz–Gilbert Equations via Convolution Quadrature: Weak Form and Numerical Approximation,”10.1515/cmam-2022-0145__Computational Methods in Applied Mathematics, vol. 23, no. 1, pp. 19–48, 2022, doi:10.1515/cmam-2022-0145 .

F. Nüske, P. Gelß, S. Klus, and C. Clementi, “Tensor-based computation of metastable and coherent sets,”10.1016/j.physd.2021.133018__Physica D: Nonlinear Phenomena, Art. no. 133018, 2021, doi:10.1016/j.physd.2021.133018 .

S. Klus, P. Gelß, F. Nüske, and F. Noé, “Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry,”10.1088/2632-2153/ac14ad__Machine Learning: Science and Technology, Art. no. 045016, 2021, doi:10.1088/2632-2153/ac14ad .

C. Goelz et al., “Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults,” Cognitive Neurodynamics, 2021.

M. B. Berkemeier and S. Peitz, “Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models,” Mathematical and Computational Applications, vol. 26, no. 2, 2021.

F. Nüske, P. Koltai, L. Boninsegna, and C. Clementi, “Spectral Properties of Effective Dynamics from Conditional Expectations,” Entropy, 2021.

B. Gebken and S. Peitz, “An efficient descent method for locally Lipschitz multiobjective optimization problems,” Journal of Optimization Theory and Applications, vol. 188, pp. 696–723, 2021.

B. Gebken and S. Peitz, “Inverse multiobjective optimization: Inferring decision criteria from data,” Journal of Global Optimization, vol. 80, pp. 3–29, 2021.

R. Gerlach, The Computation and Analysis of Invariant Sets of Infinite-Dimensional Systems. 2021.

J. Li, Y. Ma, Z. Miao, Y. Shi, W. Wang, and C.-Q. Zhang, “Nowhere-zero 3-flows in toroidal graphs,”10.1016/j.jctb.2021.11.001__Journal of Combinatorial Theory, Series B, vol. 153, pp. 61–80, 2021, doi:10.1016/j.jctb.2021.11.001 .

S. Ober-Blöbaum and M. Vermeeren, “Superconvergence of galerkin variational integrators,” in 7th IIFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control LHMNC, 2021, vol. 54(19), pp. 327–333.

S. Ober-Blöbaum and S. 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), pp. 380–403, 2021, doi:10.1002/rnc.5281 .

W. Djema, L. Giraldi, S. Maslovskaya, and O. Bernard, “Turnpike features in optimal selection of species represented by quota models,”10.1016/j.automatica.2021.109804__Automatica, vol. 132, Art. no. 109804, 2021, doi:10.1016/j.automatica.2021.109804 .

J. Li, Y. Ma, Y. Shi, W. Wang, and Y. Wu, “On 3-flow-critical graphs,”10.1016/j.ejc.2021.103451__European Journal of Combinatorics, vol. 100, Art. no. 103451, 2021, doi:10.1016/j.ejc.2021.103451 .

J. Klüners and T. Komatsu, “Imaginary multiquadratic number fields with class group of exponent $ and $,”10.1090/mcom/3609__Mathematics of Computation, vol. 90, no. 329, pp. 1483–1497, 2021, doi:10.1090/mcom/3609 .

M. Kirschmer, F. Narbonne, C. Ritzenthaler, and D. Robert, “Spanning the isogeny class of a power of an elliptic curve,”10.1090/mcom/3672__Mathematics of Computation, vol. 91, no. 333, pp. 401–449, 2021, doi:10.1090/mcom/3672 .

C. Offen and S. Ober-Blöbaum, “Bifurcation preserving discretisations of optimal control problems,”https://doi.org/10.1016/j.ifacol.2021.11.099__vol. 54(19). pp. 334–339, 2021, doi:https://doi.org/10.1016/j.ifacol.2021.11.099 .

S. Ridderbusch, C. Offen, S. Ober-Blöbaum, and P. Goulart, “Learning ODE Models with Qualitative Structure Using Gaussian Processes ,”10.1109/CDC45484.2021.9683426__in 2021 60th IEEE Conference on Decision and Control (CDC), Austin, TX, USA, 2021, p. 2896, doi:10.1109/CDC45484.2021.9683426 .

N. Vertovec, S. Ober-Blöbaum, and K. Margellos, “Multi-objective minimum time optimal control for low-thrust trajectory design,” Rotterdam, the Netherlands, pp. 1975–1980.

F. Jiménez and S. Ober-Blöbaum, “Fractional Damping Through Restricted Calculus of Variations,” in Nichtlineare Sci 31, 2021, vol. 46.

T. Binz and B. Kovács, “A convergent finite element algorithm for mean curvature flow in higher codimension,” arXiv, 2021.

T. Binz and B. Kovács, “A convergent finite element algorithm for generalized mean curvature flows of closed surfaces,”10.1093/imanum/drab043__IMA Journal of Numerical Analysis, vol. 42, no. 3, pp. 2545–2588, 2021, doi:10.1093/imanum/drab043 .

P. Harder and B. Kovács, “Error estimates for the Cahn–Hilliard equation with dynamic boundary conditions,”10.1093/imanum/drab045__IMA Journal of Numerical Analysis, vol. 42, no. 3, pp. 2589–2620, 2021, doi:10.1093/imanum/drab045 .

J. Nick, B. Kovács, and C. Lubich, “Correction to: Stable and convergent fully discrete interior–exterior coupling of Maxwell’s equations,”10.1007/s00211-021-01196-6__Numerische Mathematik, vol. 147, no. 4, pp. 997–1000, 2021, doi:10.1007/s00211-021-01196-6 .

B. Kovács, B. Li, and C. Lubich, “A convergent evolving finite element algorithm for Willmore flow of closed surfaces,”10.1007/s00211-021-01238-z__Numerische Mathematik, vol. 149, no. 3, pp. 595–643, 2021, doi:10.1007/s00211-021-01238-z .

R. I. McLachlan and C. Offen, “Preservation of Bifurcations of Hamiltonian Boundary Value Problems Under Discretisation,” Foundations of Computational Mathematics, vol. 20, no. 6, pp. 1363–1400, 2020.

L. M. Kreusser, R. I. McLachlan, and C. Offen, “Detection of high codimensional bifurcations in variational PDEs,” Nonlinearity, vol. 33, no. 5, pp. 2335–2363, 2020.

K. Flaßkamp, S. Ober-Blöbaum, and S. Peitz, “Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach,” in Advances in Dynamics, Optimization and Computation, O. Junge, O. Schütze, G. Froyland, S. Ober-Blöbaum, and K. Padberg-Gehle, Eds. Cham: Springer, 2020.

S. Klus, F. Nüske, and B. Hamzi, “Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator,” Entropy, 2020.

O. Schütze, O. Cuate, A. Martín, S. Peitz, and M. Dellnitz, “Pareto Explorer: a global/local exploration tool for many-objective optimization problems,” Engineering Optimization, vol. 52, no. 5, pp. 832–855, 2020.

S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, and C. Schütte, “Data-driven approximation of the Koopman generator: Model reduction, system identification, and control,” Physica D: Nonlinear Phenomena, vol. 406, 2020.