On the importance of hyperparameter optimization for model-based reinforcement learning B Zhang, R Rajan, L Pineda, N Lambert, A Biedenkapp, K Chua, F Hutter, ... International Conference on Artificial Intelligence and Statistics, 4015-4023, 2021 | 106 | 2021 |
Automated reinforcement learning (autorl): A survey and open problems J Parker-Holder, R Rajan, X Song, A Biedenkapp, Y Miao, T Eimer, ... Journal of Artificial Intelligence Research 74, 517-568, 2022 | 78 | 2022 |
TempoRL: Learning when to act A Biedenkapp, R Rajan, F Hutter, M Lindauer International Conference on Machine Learning, 914-924, 2021 | 30 | 2021 |
Towards temporl: Learning when to act A Biedenkapp, R Rajan, F Hutter, M Lindauer Workshop on Inductive Biases, Invariances and Generalization in …, 2020 | 9 | 2020 |
MDP Playground: Meta-Features in Reinforcement Learning. R Rajan, F Hutter arXiv preprint arXiv:1909.07750, 2019 | 5* | 2019 |
T3VIP: Transformation-based Video Prediction I Nematollahi, E Rosete-Beas, SMB Azad, R Rajan, F Hutter, W Burgard 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 2 | 2022 |
Dreaming of Many Worlds: Learning Contextual World Models Aids Zero-Shot Generalization S Prasanna, K Farid, R Rajan, A Biedenkapp arXiv preprint arXiv:2403.10967, 2024 | 1 | 2024 |