Gebken, Bennet. “A Note on the Convergence of Deterministic Gradient Sampling in Nonsmooth Optimization.”https://doi.org/10.1007/s10589-024-00552-0__Computational Optimization and Applications, 2024.https://doi.org/10.1007/s10589-024-00552-0 .

Sonntag, Konstantin, Bennet Gebken, Georg Müller, Sebastian Peitz, and Stefan Volkwein. “A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces.” ArXiv:2402.06376, 2024.

Gebken, Bennet, Katharina Bieker, and Sebastian Peitz. “On the Structure of Regularization Paths for Piecewise Differentiable Regularization Terms.”https://doi.org/10.1007/s10898-022-01223-2__Journal of Global Optimization 85, no. 3 (2023): 709–41.https://doi.org/10.1007/s10898-022-01223-2 .

Bernreuther, Marco, Michael Dellnitz, Bennet Gebken, Georg Müller, Sebastian Peitz, Konstantin Sonntag, and Stefan Volkwein. “Multiobjective Optimization of Non-Smooth PDE-Constrained Problems.” ArXiv:2308.01113, 2023.

Banholzer, Stefan, Bennet Gebken, Michael Dellnitz, Sebastian Peitz, and Stefan Volkwein. “ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation.”https://doi.org/10.1007/978-3-030-79393-7_3__In Non-Smooth and Complementarity-Based Distributed Parameter Systems, edited by Hintermüller Michael, Herzog Roland, Kanzow Christian, Ulbrich Michael, and Ulbrich Stefan, 43–76. Cham: Springer, 2022.https://doi.org/10.1007/978-3-030-79393-7_3 .

Gebken, Bennet. “Using Second-Order Information in Gradient Sampling Methods for  Nonsmooth Optimization.” ArXiv:2210.04579, 2022.

Gebken, Bennet. Computation and Analysis of Pareto Critical Sets in Smooth and Nonsmooth Multiobjective Optimization, 2022.https://doi.org/10.17619/UNIPB/1-1327 .

Bieker, Katharina, Bennet Gebken, and Sebastian Peitz. “On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation.”https://doi.org/10.1109/TPAMI.2021.3114962__IEEE Transactions on Pattern Analysis and Machine Intelligence 44, no. 11 (2022): 7797–7808.https://doi.org/10.1109/TPAMI.2021.3114962 .

Gebken, Bennet, and Sebastian Peitz. “An Efficient Descent Method for Locally Lipschitz Multiobjective Optimization Problems.”https://doi.org/10.1007/s10957-020-01803-w__Journal of Optimization Theory and Applications 188 (2021): 696–723.https://doi.org/10.1007/s10957-020-01803-w .

Gebken, Bennet, and Sebastian Peitz. “Inverse Multiobjective Optimization: Inferring Decision Criteria from Data.”https://doi.org/10.1007/s10898-020-00983-z__Journal of Global Optimization 80 (2021): 3–29.https://doi.org/10.1007/s10898-020-00983-z .

Dellnitz, Michael, Bennet Gebken, Raphael Gerlach, and Stefan Klus. “On the Equivariance Properties of Self-Adjoint Matrices.”https://doi.org/10.1080/14689367.2019.1661355__Dynamical Systems 35, no. 2 (2020): 197–215.https://doi.org/10.1080/14689367.2019.1661355 .

Gebken, Bennet, Sebastian Peitz, and Michael Dellnitz. “On the Hierarchical Structure of Pareto Critical Sets.”https://doi.org/10.1007/s10898-019-00737-6__Journal of Global Optimization 73, no. 4 (2019): 891–913.https://doi.org/10.1007/s10898-019-00737-6 .

Gebken, Bennet, Sebastian Peitz, and Michael Dellnitz. “A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems.”https://doi.org/10.1007/978-3-319-96104-0_2__In Numerical and Evolutionary Optimization – NEO 2017. Cham, 2018.https://doi.org/10.1007/978-3-319-96104-0_2 .