Caleb Chuck

22 papers A* 4A 2C 1Misc 1Journal 12Unranked 2
YearRankTypeTitle / Venue / Authors
2025 A* conf
Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning.
ICLR
Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal, Amy Zhang, Scott Niekum
2025 J jnl
Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning.
CoRR
Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal, Amy Zhang, Scott Niekum
2024 Misc conf
A Dual Approach to Imitation Learning from Observations with Offline Datasets.
CoRL
Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum
2024 J jnl
A Dual Approach to Imitation Learning from Observations with Offline Datasets.
CoRR
Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum
2024 J jnl
Automated Discovery of Functional Actual Causes in Complex Environments.
CoRR
Caleb Chuck, Sankaran Vaidyanathan, Stephen Giguere, Amy Zhang, David Jensen, Scott Niekum
2024 A conf
Gaze Supervision for Mitigating Causal Confusion in Driving Agents.
AAMAS
Abhijat Biswas, Badal Arun Pardhi, Caleb Chuck, Jarrett Holtz, Scott Niekum, Henny Admoni, Alessandro Allievi
2024 C conf
Gaze Supervision for Mitigating Causal Confusion in Driving Agents.
IV
Abhijat Biswas, Badal Arun Pardhi, Caleb Chuck, Jarrett Holtz, Scott Niekum, Henny Admoni, Alessandro Allievi
2024 J jnl
Granger Causal Interaction Skill Chains.
Trans. Mach. Learn. Res.
Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum
2024 J jnl
Learning Action-based Representations Using Invariance.
RLJ
Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang
2024 J jnl
Learning Action-based Representations Using Invariance.
CoRR
Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang
2024 J jnl
RL Zero: Zero-Shot Language to Behaviors without any Supervision.
CoRR
Harshit Sikchi, Siddhant Agarwal, Pranaya Jajoo, Samyak Parajuli, Caleb Chuck, Max Rudolph, Peter Stone, Amy Zhang, Scott Niekum
2024 J jnl
Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning.
CoRR
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
2024 A* conf
SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions.
NeurIPS
Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone
2024 J jnl
SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions.
CoRR
Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone
2023 J jnl
Granger-Causal Hierarchical Skill Discovery.
CoRR
Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum
2021 A* conf
ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory.
ICRA
Ajinkya Jain, Rudolf Lioutikov, Caleb Chuck, Scott Niekum
2020 A conf
Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning.
IROS
Caleb Chuck, Supawit Chockchowwat, Scott Niekum
2019 J jnl
Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning.
CoRR
Caleb Chuck, Supawit Chockchowwat, Scott Niekum
2017 A* conf
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations.
ICRA
Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin Jamieson, Anca D. Dragan, Ken Goldberg
2017 — conf
Statistical data cleaning for deep learning of automation tasks from demonstrations.
CASE
Caleb Chuck, Michael Laskey, Sanjay Krishnan, Ruta Joshi, Roy Fox, Ken Goldberg
2016 J jnl
Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations.
CoRR
Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin Jamieson, Anca D. Dragan, Kenneth Y. Goldberg
2016 — conf
Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations.
CASE
Michael Laskey, Jonathan Lee, Caleb Chuck, David V. Gealy, Wesley Yu-Shu Hsieh, Florian T. Pokorny, Anca D. Dragan, Ken Goldberg