Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations. - Michael Laskey; Jonathan Lee 002; Caleb Chuck; David V. Gealy; Wesley Yu-Shu Hsieh; Florian T. Pokorny; Anca D. Dragan; Ken Goldberg (CASE, 2016)

Statistical data cleaning for deep learning of automation tasks from demonstrations. - Caleb Chuck; Michael Laskey; Sanjay Krishnan; Ruta Joshi; Roy Fox; Ken Goldberg (CASE, 2017)

Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations. - Michael Laskey; Caleb Chuck; Jonathan Lee 002; Jeffrey Mahler; Sanjay Krishnan; Kevin G. Jamieson; Anca D. Dragan; Ken Goldberg (ICRA, 2017)

Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning. - Caleb Chuck; Supawit Chockchowwat; Scott Niekum (IROS, 2020)

ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory. - Ajinkya Jain; Rudolf Lioutikov; Caleb Chuck; Scott Niekum (ICRA, 2021)

Granger-Causal Hierarchical Skill Discovery. - Caleb Chuck; Kevin Black; Aditya Arjun; Yuke Zhu; Scott Niekum (CoRR, 2023)

A Dual Approach to Imitation Learning from Observations with Offline Datasets. - Harshit Sikchi; Caleb Chuck; Amy Zhang 001; Scott Niekum (CoRL, 2024)

Gaze Supervision for Mitigating Causal Confusion in Driving Agents. - Abhijat Biswas; Badal Arun Pardhi; Caleb Chuck; Jarrett Holtz; Scott Niekum; Henny Admoni; Alessandro Allievi (IV, 2024)

SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions. - Zizhao Wang; Jiaheng Hu; Caleb Chuck; Stephen Chen; Roberto Martín-Martín; Amy Zhang 001; Scott Niekum; Peter Stone 001 (NeurIPS, 2024)

Learning Action-based Representations Using Invariance. - Max Rudolph; Caleb Chuck; Kevin Black; Misha Lvovsky; Scott Niekum; Amy Zhang 001 (RLJ, 2024)

Automated Discovery of Functional Actual Causes in Complex Environments. - Caleb Chuck; Sankaran Vaidyanathan; Stephen Giguere 001; Amy Zhang 001; David Jensen; Scott Niekum (CoRR, 2024)

Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning. - 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; et al. (CoRR, 2024)

RL Zero: Zero-Shot Language to Behaviors without any Supervision. - Harshit Sikchi; Siddhant Agarwal; Pranaya Jajoo; Samyak Parajuli; Caleb Chuck; Max Rudolph; Peter Stone 001; Amy Zhang 001; Scott Niekum (CoRR, 2024)

Granger Causal Interaction Skill Chains. - Caleb Chuck; Kevin Black; Aditya Arjun; Yuke Zhu; Scott Niekum (Trans. Mach. Learn. Res., 2024)

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning. - Caleb Chuck; Fan Feng; Carl Qi; Chang Shi; Siddhant Agarwal; Amy Zhang 001; Scott Niekum (ICLR, 2025)