Jonathan Tompson
My research background covers a wide range of topics: computer vision and graphics, robotics, computational fluid dynamics, reinforcement learning, unsupervised learning, hand and human body tracking and analog IC design.
You can find more of my projects at jonathantompson.com.
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Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models
Harris Chan
Anthony Brohan
Karol Hausman
Sergey Levine
RSS 2023 (2023)
InnerMonologue: Embodied Reasoning through Planning with Language Models
Wenlong Huang
Harris Chan
Jacky Liang
Pete Florence
Andy Zeng
Igor Mordatch
Yevgen Chebotar
Noah Brown
Tomas Jackson
Linda Luu
Sergey Levine
Karol Hausman
Brian Andrew Ichter
Conference on Robot Learning (2022) (to appear)
XIRL: Cross-embodiment Inverse Reinforcement Learning
Kevin Zakka
Andy Zeng
Pete Florence
Jeannette Bohg
CORL (2021)
Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks
Daniel Seita
Pete Florence
Erwin Johan Coumans
Ken Goldberg
Andy Zeng
IEEE International Conference on Robotics and Automation (ICRA) (2021)
Implicit Behavioral Cloning
Pete Florence
Corey Lynch
Andy Zeng
Oscar Ramirez
Laura Downs
Igor Mordatch
CoRL (2021)
Imitation Learning via Off-Policy Distribution Matching
Ilya Kostrikov
Ofir Nachum
Submission for NeurIPS workshop, ICLR conference (2020)
Counting Out Time: Class Agnostic Video Periodicity in the Wild
Yusuf Aytar
Andrew Zisserman
CVPR (2020)
Transporter Networks: Rearranging the Visual World for Robotic Manipulation
Andy Zeng
Pete Florence
Stefan Welker
Jonathan Chien
Travis Armstrong
Ivan Krasin
Dan Duong
Conference on Robot Learning (CoRL) (2020)
