| Self-paced contextual reinforcement learning P Klink, H Abdulsamad, B Belousov, J Peters Conference on Robot Learning, 513-529, 2019 | 41 | 2019 |
| Self-Paced Deep Reinforcement Learning P Klink, C D'Eramo, J Peters, J Pajarinen Advances in Neural Information Processing Systems, 9216--9227, 2020 | 27 | 2020 |
| Reinforcement learning algorithms: analysis and applications B Belousov, H Abdulsamad, P Klink, S Parisi, J Peters Springer, 2021 | 16 | 2021 |
| 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 | 14 | 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 | 13 | 2021 |
| 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 | 6 | 2022 |
| 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 | 5 | 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 | 4 | 2020 |
| Boosted curriculum reinforcement learning P Klink, C D'Eramo, J Peters, J Pajarinen International Conference on Learning Representations, 2022 | 3 | 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 | 3 | 2021 |
| Model-Based Reinforcement Learning from PILCO to PETS P Klink Reinforcement Learning Algorithms: Analysis and Applications, 165-175, 2021 | 3 | 2021 |
