Pascal Klink
Title
Cited by
Cited by
Year
Self-paced contextual reinforcement learning
P Klink, H Abdulsamad, B Belousov, J Peters
Conference on Robot Learning, 513-529, 2020
112020
Self-Paced Deep Reinforcement Learning
P Klink, C D'Eramo, J Peters, J Pajarinen
arXiv preprint arXiv:2004.11812, 2020
32020
Generalized Mean Estimation in Monte-Carlo Tree Search
T Dam, P Klink, C D'Eramo, J Peters, J Pajarinen
arXiv preprint arXiv:1911.00384, 2019
12019
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
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
arXiv preprint arXiv:2102.13176, 2021
2021
Model-Based Reinforcement Learning from PILCO to PETS
P Klink
Reinforcement Learning Algorithms: Analysis and Applications, 165-175, 2021
2021
A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning
H Abdulsamad, P Nickl, P Klink, J Peters
arXiv preprint arXiv:2011.05217, 2020
2020
Neural Linear Models with Functional Gaussian Process Priors
J Watson, JA Lin, P Klink, J Peters
Reinforcement Learning Algorithms: Analysis and Applications
B Belousov, H Abdulsamad, P Klink, S Parisi, J Peters
Springer Nature, 0
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