| 2025 | ICLR | Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning. | Wesley A. Suttle, Aamodh Suresh, Carlos Nieto-Granda |
| 2025 | IROS | Confidence-Controlled Exploration: Efficient Sparse-Reward Policy Learning for Robot Navigation. | Bhrij Patel, Kasun Weerakoon, Wesley A. Suttle, Alec Koppel, Brian M. Sadler, Tianyi Zhou, Dinesh Manocha, Amrit Singh Bedi |
| 2025 | ISIT | An Analysis of Plug-in and Bias-corrected Fixed-k Nearest Neighbor Density Functional Estimators. | Wesley A. Suttle |
| 2024 | ICML | Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles. | Bhrij Patel, Wesley A. Suttle, Alec Koppel, Vaneet Aggarwal, Brian M. Sadler, Dinesh Manocha, Amrit S. Bedi |
| 2024 | ICML | PIPER: Primitive-Informed Preference-based Hierarchical Reinforcement Learning via Hindsight Relabeling. | Utsav Singh, Wesley A. Suttle, Brian M. Sadler, Vinay P. Namboodiri, Amrit S. Bedi |
| 2024 | IROS | LANCAR: Leveraging Language for Context-Aware Robot Locomotion in Unstructured Environments. | Chak Lam Shek, Xiyang Wu, Wesley A. Suttle, Carl E. Busart, Erin G. Zaroukian, Dinesh Manocha, Pratap Tokekar, Amrit Singh Bedi |
| 2023 | CISS | Information-Directed Policy Search in Sparse-Reward Settings via the Occupancy Information Ratio. | Wesley A. Suttle, Alec Koppel, Ji Liu |
| 2023 | ICML | Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic. | Wesley A. Suttle, Amrit S. Bedi, Bhrij Patel, Brian M. Sadler, Alec Koppel, Dinesh Manocha |
| 2022 | CISS | Policy Gradient for Ratio Optimization: A Case Study. | Wesley A. Suttle, Alec Koppel, Ji Liu |