Caleb Chuck

According to our database, Caleb Chuck authored at least 7 papers between 2016 and 2024.

Collaborative distances:

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

2024

Learning Action-based Representations Using Invariance.

Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang

CoRR, 2024

2023

Granger-Causal Hierarchical Skill Discovery.

Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum

CoRR, 2023

2021

ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory.

Ajinkya Jain, Rudolf Lioutikov, Caleb Chuck, Scott Niekum

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020

Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning.

Caleb Chuck, Supawit Chockchowwat, Scott Niekum

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

2017

Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations.

Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin G. Jamieson, Anca D. Dragan, Ken Goldberg

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Statistical data cleaning for deep learning of automation tasks from demonstrations.

Caleb Chuck, Michael Laskey, Sanjay Krishnan, Ruta Joshi, Roy Fox, Ken Goldberg

Proceedings of the 13th IEEE Conference on Automation Science and Engineering, 2017

2016

Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations.

Michael Laskey, Jonathan Lee, Caleb Chuck, David V. Gealy, Wesley Yu-Shu Hsieh, Florian T. Pokorny, Anca D. Dragan, Ken Goldberg

Proceedings of the IEEE International Conference on Automation Science and Engineering, 2016