Jonathan Scholz

According to our database, Jonathan Scholz authored at least 27 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation.

Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Manon Devin, Alex X. Lee, Maria Bauzá Villalonga, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo Fernandes Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, José Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess

Trans. Mach. Learn. Res., 2024

DemoStart: Demonstration-led auto-curriculum applied to sim-to-real with multi-fingered robots.

Maria Bauzá, José Enrique Chen, Valentin Dalibard, Nimrod Gileadi, Roland Hafner, Murilo F. Martins, Joss Moore, Rugile Pevceviciute, Antoine Laurens, Dushyant Rao, Martina Zambelli, Martin A. Riedmiller, Jon Scholz, Konstantinos Bousmalis, Francesco Nori, Nicolas Heess

CoRR, 2024

RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation.

Mel Vecerík, Carl Doersch, Yi Yang, Todor Davchev, Yusuf Aytar, Guangyao Zhou, Raia Hadsell, Lourdes Agapito, Jon Scholz

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks.

Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerík, Jonathan Scholz, David Held

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation.

Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Devin, Alex X. Lee, Maria Bauzá, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo F. Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, José Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess

CoRR, 2023

Lossless Adaptation of Pretrained Vision Models For Robotic Manipulation.

Mohit Sharma, Claudio Fantacci, Yuxiang Zhou, Skanda Koppula, Nicolas Heess, Jon Scholz, Yusuf Aytar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Offline Meta-Reinforcement Learning for Industrial Insertion.

Tony Z. Zhao, Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Nicolas Heess, Jon Scholz, Stefan Schaal, Sergey Levine

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Few-Shot Keypoint Detection as Task Adaptation via Latent Embeddings.

Mel Vecerík, Jackie Kay, Raia Hadsell, Lourdes Agapito, Jon Scholz

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Wish you were here: Hindsight Goal Selection for long-horizon dexterous manipulation.

Todor Davchev, Oleg Olegovich Sushkov, Jean-Baptiste Regli, Stefan Schaal, Yusuf Aytar, Markus Wulfmeier, Jon Scholz

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study.

Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Wenzhao Lian, Chang Su, Mel Vecerík, Ning Ye, Stefan Schaal, Jonathan Scholz

Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

2020

S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency.

Mel Vecerík, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Christopher Schuster, Raia Hadsell, Lourdes Agapito, Jonathan Scholz

CoRR, 2020

Scaling data-driven robotics with reward sketching and batch reinforcement learning.

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

Proceedings of the Robotics: Science and Systems XVI, 2020

S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency.

Mel Vecerík, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Raia Hadsell, Lourdes Agapito, Jonathan Scholz

Proceedings of the 4th Conference on Robot Learning, 2020

2019

A Framework for Data-Driven Robotics.

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

CoRR, 2019

Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient.

Kevin Sebastian Luck, Mel Vecerík, Simon Stepputtis, Heni Ben Amor, Jonathan Scholz

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning.

Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz

Proceedings of the International Conference on Robotics and Automation, 2019

Generative predecessor models for sample-efficient imitation learning.

Yannick Schroecker, Mel Vecerík, Jonathan Scholz

Proceedings of the 7th International Conference on Learning Representations, 2019

2017

Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards.

Matej Vecerík, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin A. Riedmiller

CoRR, 2017

PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations.

Rico Jonschkowski, Roland Hafner, Jonathan Scholz, Martin A. Riedmiller

CoRR, 2017

2016

Navigation Among Movable Obstacles with learned dynamic constraints.

Jonathan Scholz, Nehchal Jindal, Martin Levihn, Charles L. Isbell Jr., Henrik I. Christensen

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

2015

Learning non-holonomic object models for mobile manipulation.

Jonathan Scholz, Martin Levihn, Charles L. Isbell Jr., Henrik I. Christensen, Mike Stilman

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014

A Physics-Based Model Prior for Object-Oriented MDPs.

Jonathan Scholz, Martin Levihn, Charles Lee Isbell Jr., David Wingate

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Policy Shaping: Integrating Human Feedback with Reinforcement Learning.

Shane Griffith, Kaushik Subramanian, Jonathan Scholz, Charles L. Isbell Jr., Andrea Lockerd Thomaz

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Planning with movable obstacles in continuous environments with uncertain dynamics.

Martin Levihn, Jonathan Scholz, Mike Stilman

Proceedings of the 2013 IEEE International Conference on Robotics and Automation, 2013

2012

Hierarchical Decision Theoretic Planning for Navigation Among Movable Obstacles.

Martin Levihn, Jonathan Scholz, Mike Stilman

Proceedings of the Algorithmic Foundations of Robotics X, 2012

2011

Cart pushing with a mobile manipulation system: Towards navigation with moveable objects.

Jonathan Scholz, Sachin Chitta, Bhaskara Marthi, Maxim Likhachev

Proceedings of the IEEE International Conference on Robotics and Automation, 2011

2010

Combining motion planning and optimization for flexible robot manipulation.

Jonathan Scholz, Mike Stilman

Proceedings of the 10th IEEE-RAS International Conference on Humanoid Robots, 2010