Jonathan Scholz

28 papers A* 6A 2C 1Misc 1Journal 12Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	RoboBallet: Planning for Multi-Robot Reaching with Graph Neural Networks and Reinforcement Learning. CoRR Matthew Lai, Keegan Go, Zhibin Li, Torsten Kröger, Stefan Schaal, Kelsey Allen, Jonathan Scholz
2025	J	`jnl`	RoboBallet: Planning for multirobot reaching with graph neural networks and reinforcement learning. Sci. Robotics Matthew Lai, Keegan Go, Zhibin Li, Torsten Kröger, Stefan Schaal, Kelsey Allen, Jonathan Scholz
2024	A*	`conf`	Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks. ICLR Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerík, Jonathan Scholz, David Held
2024	J	`jnl`	Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks. CoRR Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerík, Jonathan Scholz, David Held
2021	J	`jnl`	Offline Meta-Reinforcement Learning for Industrial Insertion. CoRR Tony Z. Zhao, Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Nicolas Heess, Jonathan Scholz, Stefan Schaal, Sergey Levine
2021	—	`conf`	Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study. Robotics: Science and Systems Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Wenzhao Lian, Chang Su, Mel Vecerík, Ning Ye, Stefan Schaal, Jonathan Scholz
2021	J	`jnl`	Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study. CoRR Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Wenzhao Lian, Chang Su, Mel Vecerík, Ning Ye, Stefan Schaal, Jonathan Scholz
2020	Misc	`conf`	S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency. CoRL Mel Vecerík, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Raia Hadsell, Lourdes Agapito, Jonathan Scholz
2020	J	`jnl`	S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency. CoRR Mel Vecerík, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Christopher Schuster, Raia Hadsell, Lourdes Agapito, Jonathan Scholz
2020	—	`conf`	Scaling data-driven robotics with reward sketching and batch reinforcement learning. Robotics: Science and Systems Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott E. Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerík, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang
2019	J	`jnl`	A Framework for Data-Driven Robotics. CoRR Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott E. Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerík, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang
2019	A*	`conf`	A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning. ICRA Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz
2019	—	`conf`	Generative predecessor models for sample-efficient imitation learning. ICLR (Poster) Yannick Schroecker, Mel Vecerík, Jonathan Scholz
2019	J	`jnl`	Generative predecessor models for sample-efficient imitation learning. CoRR Yannick Schroecker, Mel Vecerík, Jonathan Scholz
2019	A	`conf`	Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient. IROS Kevin Sebastian Luck, Mel Vecerík, Simon Stepputtis, Heni Ben Amor, Jonathan Scholz
2019	J	`jnl`	Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient. CoRR Kevin Sebastian Luck, Mel Vecerík, Simon Stepputtis, Heni Ben Amor, Jonathan Scholz
2018	J	`jnl`	A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning. CoRR Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz
2017	J	`jnl`	Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards. CoRR Matej Vecerík, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin A. Riedmiller
2017	J	`jnl`	PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations. CoRR Rico Jonschkowski, Roland Hafner, Jonathan Scholz, Martin A. Riedmiller
2016	A	`conf`	Navigation Among Movable Obstacles with learned dynamic constraints. IROS Jonathan Scholz, Nehchal Jindal, Martin Levihn, Charles L. Isbell Jr., Henrik I. Christensen
2016	—	`—`	Physics-based reinforcement learning for autonomous manipulation. Jonathan Scholz
2015	A*	`conf`	Learning non-holonomic object models for mobile manipulation. ICRA Jonathan Scholz, Martin Levihn, Charles L. Isbell Jr., Henrik I. Christensen, Mike Stilman
2014	A*	`conf`	A Physics-Based Model Prior for Object-Oriented MDPs. ICML Jonathan Scholz, Martin Levihn, Charles Lee Isbell Jr., David Wingate
2013	A*	`conf`	Planning with movable obstacles in continuous environments with uncertain dynamics. ICRA Martin Levihn, Jonathan Scholz, Mike Stilman
2013	—	`conf`	Policy Shaping: Integrating Human Feedback with Reinforcement Learning. NIPS Shane Griffith, Kaushik Subramanian, Jonathan Scholz, Charles L. Isbell Jr., Andrea Lockerd Thomaz
2012	C	`conf`	Hierarchical Decision Theoretic Planning for Navigation Among Movable Obstacles. WAFR Martin Levihn, Jonathan Scholz, Mike Stilman
2011	A*	`conf`	Cart pushing with a mobile manipulation system: Towards navigation with moveable objects. ICRA Jonathan Scholz, Sachin Chitta, Bhaskara Marthi, Maxim Likhachev
2010	—	`conf`	Combining motion planning and optimization for flexible robot manipulation. Humanoids Jonathan Scholz, Mike Stilman