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

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 .

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

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.

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.

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 .

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.

M. Dellnitz, B. Gebken, R. Gerlach, and S. Klus, “On the equivariance properties of self-adjoint matrices,”10.1080/14689367.2019.1661355__Dynamical Systems, vol. 35, no. 2, pp. 197–215, 2020, doi:10.1080/14689367.2019.1661355 .

B. Gebken, S. Peitz, and M. Dellnitz, “On the hierarchical structure of Pareto critical sets,” Journal of Global Optimization, vol. 73, no. 4, pp. 891–913, 2019.

B. Gebken, S. Peitz, and M. Dellnitz, “A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems,” in Numerical and Evolutionary Optimization – NEO 2017, 2018.