| A recurrent machine learning model predicts intracranial hypertension in neurointensive care patients N Schweingruber, MMD Mader, A Wiehe, F Röder, J Göttsche, S Kluge, ... Brain 145 (8), 2910-2919, 2022 | 25 | 2022 |
| Curious Hierarchical Actor-Critic Reinforcement Learning F Röder, M Eppe, PDH Nguyen, S Wermter International Conference on Artificial Neural Networks 12397, 408--419, 2020 | 25 | 2020 |
| The Embodied Crossmodal Self Forms Language and Interaction: A Computational Cognitive Review F Röder, O Özdemir, PDH Nguyen, S Wermter, M Eppe Frontiers in Psychology 12, 3374, 2021 | 8 | 2021 |
| Grounding Hindsight Instructions in Multi-Goal Reinforcement Learning for Robotics F Röder, M Eppe, S Wermter International Conference on Development and Learning, 170-177, 2022 | 7 | 2022 |
| Language-Conditioned Reinforcement Learning to Solve Misunderstandings with Action Corrections F Röder, M Eppe Conference on Neural Information Processing Systems - Second Workshop on …, 2022 | 2 | 2022 |
| Scilab-RL: A software framework for efficient reinforcement learning and cognitive modeling research J Dohmen, F Röder, M Eppe arXiv preprint arXiv:2401.14488, 2024 | | 2024 |
| Model-Based Hierarchical Actor-Critic Reinforcement Learning F Röder University of Hamburg, 2020 | | 2020 |
| Static Code Analysis for HPC Use Cases F Röder University of Hamburg, 2017 | | 2017 |
Manfred EppeHamburg University of TechnologyVerified email at tuhh.de
