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ORCIDDaniel Palenicek
Person information
- affiliation: TU Darmstadt, Germany
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2020 – today
- 2024
[c4]Aditya Bhatt, Daniel Palenicek, Boris Belousov, Max Argus, Artemij Amiranashvili, Thomas Brox, Jan Peters:
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity. ICLR 2024- [i9]Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo:
Iterated Q-Network: Beyond the One-Step Bellman Operator. CoRR abs/2403.02107 (2024) - [i8]Daniel Palenicek, Theo Gruner, Tim Schneider, Alina Böhm, Janis Lenz, Inga Pfenning, Eric Krämer, Jan Peters:
Learning Tactile Insertion in the Real World. CoRR abs/2405.00383 (2024) - [i7]Janis Lenz, Theo Gruner, Daniel Palenicek, Tim Schneider, Jan Peters:
Analysing the Interplay of Vision and Touch for Dexterous Insertion Tasks. CoRR abs/2410.23860 (2024) - 2023
- [c3]Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters:
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning. ICLR 2023 - [c2]Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan R. Peters:
Pseudo-Likelihood Inference. NeurIPS 2023 - [i6]Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters:
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning. CoRR abs/2303.03955 (2023) - [i5]Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan Peters:
Pseudo-Likelihood Inference. CoRR abs/2311.16656 (2023) - 2022
- [j1]Alexander I. Cowen-Rivers
, Daniel Palenicek, Vincent Moens, Mohammed Amin Abdullah, Aivar Sootla, Jun Wang, Haitham Bou-Ammar:
SAMBA: safe model-based & active reinforcement learning. Mach. Learn. 111(1): 173-203 (2022) - [i4]Daniel Palenicek, Michael Lutter, Jan Peters:
Revisiting Model-based Value Expansion. CoRR abs/2203.14660 (2022) - 2020
- [c1]Ming Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Zhengbang Zhu, Yihan Ni, Nhat M. Nguyen, Mohamed Elsayed, Haitham Ammar, Alexander I. Cowen-Rivers, Sanjeevan Ahilan, Zheng Tian, Daniel Palenicek, Kasra Rezaee, Peyman Yadmellat, Kun Shao, Dong Chen, Baokuan Zhang, Hongbo Zhang, Jianye Hao, Wulong Liu, Jun Wang:
SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving. CoRL 2020: 264-285 - [i3]Alexander I. Cowen-Rivers, Daniel Palenicek, Vincent Moens, Mohammed Amin Abdullah, Aivar Sootla, Jun Wang, Haitham Ammar:
SAMBA: Safe Model-Based & Active Reinforcement Learning. CoRR abs/2006.09436 (2020) - [i2]Ming Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Aurora Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Dong Chen, Zhengbang Zhu, Nhat M. Nguyen, Mohamed Elsayed, Kun Shao, Sanjeevan Ahilan, Baokuan Zhang, Jiannan Wu, Zhengang Fu, Kasra Rezaee, Peyman Yadmellat, Mohsen Rohani, Nicolas Perez Nieves, Yihan Ni, Seyedershad Banijamali, Alexander I. Cowen-Rivers, Zheng Tian, Daniel Palenicek, Haitham Bou-Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, Jun Wang:
SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving. CoRR abs/2010.09776 (2020)
2010 – 2019
- 2019
- [i1]Aditya Bhatt, Daniel Palenicek, Boris Belousov, Max Argus, Artemij Amiranashvili, Thomas Brox, Jan Peters:
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity. CoRR abs/1902.05605 (2019)
Coauthor Index
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