Evaluating Physics-Based, Hybrid, and Data-Driven Models for Rubber-Metal Bushings
M.C. Wohlleben, J. Schütte, M.B. Berkemeier, S. Peitz, W. Sextro, (2025).

Multi-Objective Optimization for Sparse Deep Multi-Task Learning
S.S. Hotegni, M.B. Berkemeier, S. Peitz, in: 2024 International Joint Conference on Neural Networks (IJCNN), IEEE, Yokohama, Japan, 2024, p. 9.

Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients
M.B. Berkemeier, S. Peitz, ArXiv:2208.12094 (2022).

Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models
M.B. Berkemeier, S. Peitz, Mathematical and Computational Applications 26 (2021).