| Learning from guided play: Improving exploration for adversarial imitation learning with simple auxiliary tasks T Ablett, B Chan, J Kelly IEEE Robotics and Automation Letters 8 (3), 1263-1270, 2023 | 16* | 2023 |
| Toward Understanding In-context vs. In-weight Learning B Chan*, X Chen*, A György, D Schuurmans International Conference on Learning Representations (ICLR), 2025 | 11 | 2025 |
| Heteroscedastic uncertainty for robust generative latent dynamics O Limoyo, B Chan, F Marić, B Wagstaff, AR Mahmood, J Kelly IEEE Robotics and Automation Letters 5 (4), 6654-6661, 2020 | 8 | 2020 |
| Offline-to-online Reinforcement Learning for Image-based Grasping with Scarce Demonstrations B Chan, A Leung, J Bergstra CoRL 2024 Workshop on Mastering Robot Manipulation in a World of Abundant Data, 2024 | 2 | 2024 |
| Efficient Imitation Without Demonstrations via Value-Penalized Auxiliary Control from Examples T Ablett, B Chan, JH Wang, J Kelly International Conference on Robotics and Automation (ICRA), 2025 | 1* | 2025 |
| Mitigating the curse of horizon in Monte-Carlo returns A Ayoub*, D Szepesvari*, F Zanini*, B Chan*, D Gupta, BC da Silva, ... Reinforcement Learning Conference (RLC), 2024 | 1 | 2024 |
| A Statistical Guarantee for Representation Transfer in Multitask Imitation Learning B Chan, K Pereida, J Bergstra NeurIPS 2023 Workshop on Robot Learning, 2023 | 1 | 2023 |
| AVG-DICE: Stationary Distribution Correction by Regression F Che, B Chan, C Ma, AR Mahmood Reinforcement Learning Conference (RLC), 2025 | | 2025 |
Dale SchuurmansGoogle DeepMind & University of AlbertaVerified email at ualberta.ca
