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Caleb Chuck
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Journal Articles
- 2024
- [j1]Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum:
Granger Causal Interaction Skill Chains. Trans. Mach. Learn. Res. 2024 (2024)
Conference and Workshop Papers
- 2024
- [c7]Abhijat Biswas, Badal Arun Pardhi, Caleb Chuck, Jarrett Holtz, Scott Niekum, Henny Admoni, Alessandro Allievi:
Gaze Supervision for Mitigating Causal Confusion in Driving Agents. AAMAS 2024: 2159-2161 - [c6]Abhijat Biswas, Badal Arun Pardhi, Caleb Chuck, Jarrett Holtz, Scott Niekum, Henny Admoni, Alessandro Allievi:
Gaze Supervision for Mitigating Causal Confusion in Driving Agents. IV 2024: 2331-2338 - 2021
- [c5]Ajinkya Jain, Rudolf Lioutikov, Caleb Chuck, Scott Niekum:
ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory. ICRA 2021: 13670-13677 - 2020
- [c4]Caleb Chuck, Supawit Chockchowwat, Scott Niekum:
Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning. IROS 2020: 5572-5579 - 2017
- [c3]Caleb Chuck, Michael Laskey, Sanjay Krishnan, Ruta Joshi, Roy Fox, Ken Goldberg
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Statistical data cleaning for deep learning of automation tasks from demonstrations. CASE 2017: 1142-1149 - [c2]Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin G. Jamieson, Anca D. Dragan, Ken Goldberg:
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations. ICRA 2017: 358-365 - 2016
- [c1]Michael Laskey, Jonathan Lee, Caleb Chuck, David V. Gealy, Wesley Yu-Shu Hsieh, Florian T. Pokorny, Anca D. Dragan, Ken Goldberg:
Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations. CASE 2016: 827-834
Informal and Other Publications
- 2024
- [i7]Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang:
Learning Action-based Representations Using Invariance. CoRR abs/2403.16369 (2024) - [i6]Caleb Chuck, Sankaran Vaidyanathan, Stephen Giguere, Amy Zhang, David Jensen, Scott Niekum:
Automated Discovery of Functional Actual Causes in Complex Environments. CoRR abs/2404.10883 (2024) - [i5]Caleb Chuck, Carl Qi, Michael J. Munje, Shuozhe Li, Max Rudolph, Chang Shi, Siddhant Agarwal, Harshit Sikchi, Abhinav Peri, Sarthak Dayal, Evan Kuo, Kavan Mehta, Anthony Wang, Peter Stone, Amy Zhang, Scott Niekum:
Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning. CoRR abs/2405.03113 (2024) - [i4]Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum:
A Dual Approach to Imitation Learning from Observations with Offline Datasets. CoRR abs/2406.08805 (2024) - 2023
- [i3]Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum:
Granger-Causal Hierarchical Skill Discovery. CoRR abs/2306.09509 (2023) - 2019
- [i2]Caleb Chuck, Supawit Chockchowwat, Scott Niekum:
Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning. CoRR abs/1906.01408 (2019) - 2016
- [i1]Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin G. Jamieson, Anca D. Dragan, Kenneth Y. Goldberg:
Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations. CoRR abs/1610.00850 (2016)
Coauthor Index
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