Jonathan Scholz

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 18

Top Topics

Reinforcement Learning

Top Venues

Robotics: Science and Systems

Publications

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