Constrained Mean Shift Clustering. - Maximilian Schier; Christoph Reinders; Bodo Rosenhahn (SDM, 2022)

Deep Reinforcement Learning for Autonomous Driving using High-Level Heterogeneous Graph Representations. - Maximilian Schier; Christoph Reinders; Bodo Rosenhahn (ICRA, 2023)

Learned Fourier Bases for Deep Set Feature Extractors in Automotive Reinforcement Learning. - Maximilian Schier; Christoph Reinders; Bodo Rosenhahn (ITSC, 2023)

Safe Resetless Reinforcement Learning: Enhancing Training Autonomy with Risk-Averse Agents. - Tristan Gottwald; Maximilian Schier; Bodo Rosenhahn (ECCV Workshops (12), 2024)

Cell Tracking according to Biological Needs - Strong Mitosis-aware Random-finite Sets Tracker with Aleatoric Uncertainty. - Timo Kaiser; Maximilian Schier; Bodo Rosenhahn (CoRR, 2024)

Explainable Reinforcement Learning via Dynamic Mixture Policies. - Maximilian Schier; Frederik Schubert; Bodo Rosenhahn (ICRA, 2025)

Multi-Agent Reinforcement Learning for Inverse Design in Photonic Integrated Circuits. - Yannik Mahlau; Maximilian Schier; Christoph Reinders; Frederik Schubert; Marco Bügling; Bodo Rosenhahn (CoRR, 2025)