| Self-paced contextual reinforcement learning P Klink, H Abdulsamad, B Belousov, J Peters Conference on Robot Learning, 513-529, 2019 | 53 | 2019 |
| Self-Paced Deep Reinforcement Learning P Klink, C D'Eramo, J Peters, J Pajarinen Advances in Neural Information Processing Systems, 9216--9227, 2020 | 50 | 2020 |
| Curriculum Reinforcement Learning via Constrained Optimal Transport P Klink, H Yang, C D’Eramo, J Pajarinen, J Peters International Conference on Machine Learning (ICML), 2022 | 33 | 2022 |
| Latent Derivative Bayesian Last Layer Networks J Watson, JA Lin, P Klink, J Pajarinen, J Peters International Conference on Artificial Intelligence and Statistics, 1198-1206, 2021 | 31 | 2021 |
| Reinforcement learning algorithms: analysis and applications B Belousov, H Abdulsamad, P Klink, S Parisi, J Peters Springer, 2021 | 26 | 2021 |
| A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning P Klink, H Abdulsamad, B Belousov, C D'Eramo, J Peters, J Pajarinen Journal of Machine Learning Research 22 (182), 1-52, 2021 | 24 | 2021 |
| Neural Linear Models with Functional Gaussian Process Priors J Watson, JA Lin, P Klink, J Peters Third Symposium on Advances in Approximate Bayesian Inference, 2020 | 10 | 2020 |
| Generalized Mean Estimation in Monte-Carlo Tree Search T Dam, P Klink, C D'Eramo, J Peters, J Pajarinen International Joint Conference on Artificial Intelligence, 2397--2404, 2020 | 9 | 2020 |
| Boosted curriculum reinforcement learning P Klink, C D'Eramo, J Peters, J Pajarinen International Conference on Learning Representations, 2022 | 8 | 2022 |
| A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning H Abdulsamad, P Nickl, P Klink, J Peters 2021 IEEE International Conference on Robotics and Automation (ICRA), 4216-4222, 2021 | 5 | 2021 |
| Model-Based Reinforcement Learning from PILCO to PETS P Klink Reinforcement Learning Algorithms: Analysis and Applications, 165-175, 2021 | 4 | 2021 |
| On the Benefit of Optimal Transport for Curriculum Reinforcement Learning P Klink, C D'Eramo, J Peters, J Pajarinen IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 3 | 2024 |
| Tracking Control for a Spherical Pendulum via Curriculum Reinforcement Learning P Klink, F Wolf, K Ploeger, J Peters, J Pajarinen arXiv preprint arXiv:2309.14096, 2023 | 1 | 2023 |
| Variational Hierarchical Mixtures for Probabilistic Learning of Inverse Dynamics H Abdulsamad, P Nickl, P Klink, J Peters IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 1 | 2023 |
| Domain Randomization via Entropy Maximization G Tiboni, P Klink, J Peters, T Tommasi, C D'Eramo, G Chalvatzaki International Conference on Learning Representations, 2024 | | 2024 |
| Reinforcement Learning Curricula as Interpolations between Task Distributions P Klink Technische Universität Darmstadt, 2023 | | 2023 |
| Function-Space Regularization for Deep Bayesian Classification JA Lin, J Watson, P Klink, J Peters Symposium on Advances in Approximate Bayesian Inference (AABI), 2023 | | 2023 |
| Generalization and Transferability in Reinforcement Learning P Klink Technische Universität Darmstadt, 2019 | | 2019 |
