Selected Key References

For a more complete list, please see Google Scholar.

Aidan Scannell, Riccardo Mereu, Paul Chang, Ella Tamir, Joni Pajarinen, Arno Solin (2023). Sparse Function-space Representation of Neural Networks. DP4ML ICML 2023 Workshop.

Yi Zhao, Wenshuai Zhao, Rinu Boney, Juho Kannala, Joni Pajarinen (2023). Simplified Temporal Consistency Reinforcement Learning. In Proceedings of the International Conference on Machine Learning (ICML).

Kalle Kujanpää, Joni Pajarinen, Alexander Ilin (2023). Hierarchical Imitation Learning with Vector Quantized Models. In Proceedings of the International Conference on Machine Learning (ICML).

Abdolreza Taheri, Pelle Gustafsson, Marcus Rösth, Reza Ghabcheloo, Joni Pajarinen (2022). Nonlinear Model Learning for Compensation and Feedforward Control of Real-World Hydraulic Actuators Using Gaussian Processes. IEEE Robotics and Automation Letters.

Joni Pajarinen, Jens Lundell, Ville Kyrki (2022). POMDP planning under object composition uncertainty: Application to robotic manipulation. IEEE Transactions on Robotics.

Pascal Klink, Haoyi Yang, Carlo D'Eramo, Joni Pajarinen, Jan Peters (2022). Curriculum reinforcement learning via constrained optimal transport. In Proceedings of the International Conference on Machine Learning (ICML).

Mikko Lauri, David Hsu, Joni Pajarinen (2022). Partially Observable Markov Decision Processes in Robotics: A Survey. IEEE Transactions on Robotics.

Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen (2022). Boosted Curriculum Reinforcement Learning. International Conference on Learning Representations (ICLR).

Abdolreza Taheri, Joni Pajarinen, Reza Ghabcheloo (2022). GPU-accelerated policy optimization via batch automatic differentiation of gaussian processes for real-world control. International Conference on Robotics and Automation (ICRA).

Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen (2022). Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning. Algorithms.

Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen (2021). A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning. Journal of Machine Learning Research (JMLR).

Tuan Q Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen (2021). Convex Regularization in Monte-Carlo Tree Search. In Proceedings of the International Conference on Machine Learning (ICML).

Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen (2020). Self-Paced Deep Reinforcement Learning. In Proceedings of the Annual Conference on Neural Information Processing Systems (NeurIPS).

Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen (2020). Generalized Mean Estimation in Monte-Carlo Tree Search. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI).

Mikko Lauri, Joni Pajarinen, Jan Peters (2020). Multi-agent active information gathering in discrete and continuous-state decentralized POMDPs by policy graph improvement. Autonomous Agents and Multi-Agent Systems.

Joni Pajarinen, Oleg Arenz, Jan Peters, Gerhard Neumann (2020). Probabilistic approach to physical object disentangling. IEEE Robotics and Automation Letters.

Joni Pajarinen, Hong Linh Thai, Riad Akrour, Jan Peters, Gerhard Neumann (2019). Compatible natural gradient policy search. Machine Learning.

Riad Akrour, Joni Pajarinen, Jan Peters, Gerhard Neumann (2019). Projections for Approximate Policy Iteration Algorithms. In Proceedings of the International Conference on Machine Learning (ICML).

Dorothea Koert, Joni Pajarinen, Albert Schotschneider, Susanne Trick, Constantin Rothkopf, Jan Peters (2019). Learning Intention Aware Online Adaptation of Movement Primitives. IEEE Robotics and Automation Letters.

Takayuki Osa, Joni Pajarinen, Gerhard Neumann, J Andrew Bagnell, Pieter Abbeel, Jan Peters (2018). An Algorithmic Perspective on Imitation Learning. Foundations and Trends in Robotics.

Joni Pajarinen, Ville Kyrki, Michael Koval, Siddhartha Srinivasa, Jan Peters, Gerhard Neumann (2017). Hybrid Control Trajectory Optimization under Uncertainty. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Joni Pajarinen, Ville Kyrki (2017). Robotic manipulation of multiple objects as a POMDP. Artificial Intelligence, Elsevier.

Joni Pajarinen, Jaakko Peltonen (2011). Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning. In Annual Conference on Neural Information Processing Systems (NeurIPS).