TOAD-GAN: coherent style level generation from a single example M Awiszus, F Schubert, B Rosenhahn AIIDE 2020 16 (1), 10-16, 2020 | 45 | 2020 |
Contextualize Me – The Case for Context in Reinforcement Learning C Benjamins, T Eimer, F Schubert, A Mohan, A Biedenkapp, ... Transactions on Machine Learning Research, TMLR, 2023 | 21 | 2023 |
CARL: A benchmark for contextual and adaptive reinforcement learning C Benjamins, T Eimer, F Schubert, A Biedenkapp, B Rosenhahn, F Hutter, ... Workshop on Ecological Theory of RL, NeurIPS 2021, 2021 | 21 | 2021 |
World-GAN: a Generative Model for Minecraft Worlds M Awiszus, F Schubert, B Rosenhahn IEEE Conference on Games 2021, 2021 | 21 | 2021 |
TOAD-GAN: a flexible framework for few-shot level generation in token-based games F Schubert, M Awiszus, B Rosenhahn IEEE Transactions on Games, 2021 | 16 | 2021 |
ChimeraMix: Image Classification on Small Datasets via Masked Feature Mixing C Reinders, F Schubert, B Rosenhahn IJCAI 2022, 2022 | 6 | 2022 |
Automatic Risk Adaptation in Distributional Reinforcement Learning F Schubert, T Eimer, B Rosenhahn, M Lindauer RL4RealLife Workshop, ICML 2021, 2021 | 6 | 2021 |
POLTER: Policy Trajectory Ensemble Regularization for Unsupervised Reinforcement Learning F Schubert, C Benjamins, S Döhler, B Rosenhahn, M Lindauer Transactions on Machine Learning Research, TMLR, 2023 | 3 | 2023 |
Wor(l)d-GAN: Towards Natural Language Based PCG in Minecraft M Awiszus, F Schubert, B Rosenhahn IEEE Transactions on Games, 2022 | 2 | 2022 |
Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games Y Mahlau, F Schubert, B Rosenhahn arXiv preprint arXiv:2402.03136, 2024 | | 2024 |