Pascal Klink

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 22

Top Topics

Monte Carlo Search

Temporal Difference

Reinforcement Learning

Tracking Control

Top Venues

Publications

Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki
Domain Randomization via Entropy Maximization. ICLR (2024)
Hany Abdulsamad, Peter Nickl, Pascal Klink, Jan Peters
Variational Hierarchical Mixtures for Probabilistic Learning of Inverse Dynamics. IEEE Trans. Pattern Anal. Mach. Intell. 46 (4) (2024)
Pascal Klink, Florian Wolf, Kai Ploeger, Jan Peters, Joni Pajarinen
Tracking Control for a Spherical Pendulum via Curriculum Reinforcement Learning. CoRR (2023)
Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki
Domain Randomization via Entropy Maximization. CoRR (2023)
Tobias Niehues, Ulla Scheler, Pascal Klink
Self-Paced Absolute Learning Progress as a Regularized Approach to Curriculum Learning. CoRR (2023)
Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
On the Benefit of Optimal Transport for Curriculum Reinforcement Learning. CoRR (2023)
Jihao Andreas Lin, Joe Watson, Pascal Klink, Jan Peters
Function-Space Regularization for Deep Bayesian Classification. CoRR (2023)
Hany Abdulsamad, Peter Nickl, Pascal Klink, Jan Peters
Variational Hierarchical Mixtures for Learning Probabilistic Inverse Dynamics. CoRR (2022)
Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Boosted Curriculum Reinforcement Learning. ICLR (2022)
Pascal Klink, Haoyi Yang, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Curriculum Reinforcement Learning via Constrained Optimal Transport. ICML (2022)
Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning. J. Mach. Learn. Res. 22 (2021)
Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning. CoRR (2021)
Joe Watson, Jihao Andreas Lin, Pascal Klink, Joni Pajarinen, Jan Peters
Latent Derivative Bayesian Last Layer Networks. AISTATS (2021)
Stephan Weigand, Pascal Klink, Jan Peters, Joni Pajarinen
Reinforcement Learning using Guided Observability. CoRR (2021)
Hany Abdulsamad, Peter Nickl, Pascal Klink, Jan Peters
A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning. ICRA (2021)
Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Self-Paced Deep Reinforcement Learning. CoRR (2020)
Hany Abdulsamad, Peter Nickl, Pascal Klink, Jan Peters
A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning. CoRR (2020)
Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Generalized Mean Estimation in Monte-Carlo Tree Search. IJCAI (2020)
Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Self-Paced Deep Reinforcement Learning. NeurIPS (2020)
Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Generalized Mean Estimation in Monte-Carlo Tree Search. CoRR (2019)
Pascal Klink, Hany Abdulsamad, Boris Belousov, Jan Peters
Self-Paced Contextual Reinforcement Learning. CoRL (2019)
Pascal Klink, Hany Abdulsamad, Boris Belousov, Jan Peters
Self-Paced Contextual Reinforcement Learning. CoRR (2019)