Daniel Palenicek

25 papers A* 4A 1Misc 1Journal 19

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	StructSAM: Structure- and Spectrum-Preserving Token Merging for Segment Anything Models. CoRR Duy M. H. Nguyen, Tuan A. Tran, Duong Nguyen, Siwei Xie, Trung Q. Nguyen, Mai T. N. Truong, Daniel Palenicek, An T. Le, Michael Barz, TrungTin Nguyen, Tuan Dam, Ngan Le, Minh Vu, Khoa D. Doan, Ngo Anh Vien, Pengtao Xie, James Zou, Daniel Sonntag, Jan Peters, Mathias Niepert
2025	A*	`conf`	DIME: Diffusion-Based Maximum Entropy Reinforcement Learning. ICML Onur Celik, Zechu Li, Denis Blessing, Ge Li, Daniel Palenicek, Jan Peters, Georgia Chalvatzaki, Gerhard Neumann
2025	A	`conf`	Gait in Eight: Efficient On-Robot Learning for Omnidirectional Quadruped Locomotion. IROS Nico Bohlinger, Jonathan Kinzel, Daniel Palenicek, Lukasz Antczak, Jan Peters
2025	J	`jnl`	Gait in Eight: Efficient On-Robot Learning for Omnidirectional Quadruped Locomotion. CoRR Nico Bohlinger, Jonathan Kinzel, Daniel Palenicek, Lukasz Antczak, Jan Peters
2025	J	`jnl`	Iterated Trans. Mach. Learn. Res. Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo
2025	J	`jnl`	Scaling CrossQ with Weight Normalization. CoRR Daniel Palenicek, Florian Vogt, Jan Peters
2025	J	`jnl`	Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization. CoRR Daniel Palenicek, Florian Vogt, Jan Peters
2025	J	`jnl`	Towards Safe Robot Foundation Models Using Inductive Biases. CoRR Maximilian Tölle, Theo Gruner, Daniel Palenicek, Tim Schneider, Jonas Günster, Joe Watson, Davide Tateo, Puze Liu, Jan Peters
2025	J	`jnl`	Towards Safe Robot Foundation Models. CoRR Maximilian Tölle, Theo Gruner, Daniel Palenicek, Jonas Günster, Puze Liu, Joe Watson, Davide Tateo, Jan Peters
2025	J	`jnl`	XQC: Well-conditioned Optimization Accelerates Deep Reinforcement Learning. CoRR Daniel Palenicek, Florian Vogt, Joe Watson, Ingmar Posner, Jan Peters
2024	J	`jnl`	Analysing the Interplay of Vision and Touch for Dexterous Insertion Tasks. CoRR Janis Lenz, Theo Gruner, Daniel Palenicek, Tim Schneider, Jan Peters
2024	A*	`conf`	CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity. ICLR Aditya Bhatt, Daniel Palenicek, Boris Belousov, Max Argus, Artemij Amiranashvili, Thomas Brox, Jan Peters
2024	J	`jnl`	Diminishing Return of Value Expansion Methods. CoRR Daniel Palenicek, Michael Lutter, João Carvalho, Daniel Dennert, Faran Ahmad, Jan Peters
2024	J	`jnl`	Iterated Q-Network: Beyond the One-Step Bellman Operator. CoRR Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo
2024	J	`jnl`	Learning Tactile Insertion in the Real World. CoRR Daniel Palenicek, Theo Gruner, Tim Schneider, Alina Böhm, Janis Lenz, Inga Pfenning, Eric Krämer, Jan Peters
2023	A*	`conf`	Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning. ICLR Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters
2023	J	`jnl`	Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning. CoRR Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters
2023	A*	`conf`	Pseudo-Likelihood Inference. NeurIPS Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan R. Peters
2023	J	`jnl`	Pseudo-Likelihood Inference. CoRR Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan Peters
2022	J	`jnl`	Revisiting Model-based Value Expansion. CoRR Daniel Palenicek, Michael Lutter, Jan Peters
2022	J	`jnl`	SAMBA: safe model-based & active reinforcement learning. Mach. Learn. Alexander I. Cowen-Rivers, Daniel Palenicek, Vincent Moens, Mohammed Amin Abdullah, Aivar Sootla, Jun Wang, Haitham Bou-Ammar
2020	J	`jnl`	SAMBA: Safe Model-Based & Active Reinforcement Learning. CoRR Alexander I. Cowen-Rivers, Daniel Palenicek, Vincent Moens, Mohammed Amin Abdullah, Aivar Sootla, Jun Wang, Haitham Ammar
2020	Misc	`conf`	SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving. CoRL 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
2020	J	`jnl`	SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving. CoRR 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
2019	J	`jnl`	CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity. CoRR Aditya Bhatt, Daniel Palenicek, Boris Belousov, Max Argus, Artemij Amiranashvili, Thomas Brox, Jan Peters