| Extrapolating beyond suboptimal demonstrations via inverse reinforcement learning from observations D Brown, W Goo, P Nagarajan, S Niekum 🏆✋ International Conference on Machine Learning (ICML), 783-792, 2019 | 527 | 2019 |
| Better-than-demonstrator imitation learning via automatically-ranked demonstrations DS Brown, W Goo, S Niekum 🏆🤖 Conference on Robot Learning (CoRL), 330-359, 2020 | 282 | 2020 |
| Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences D Brown, R Coleman, R Srinivasan, S Niekum 🏆 🛡 International Conference on Machine Learning (ICML), 1165-1177, 2020 | 198* | 2020 |
| ThriftyDAgger: Budget-aware novelty and risk gating for interactive imitation learning R Hoque, A Balakrishna, E Novoseller, A Wilcox, DS Brown, K Goldberg 🤖✋ Conference on Robot Learning (CoRL), 2021 | 114 | 2021 |
| Benchmarks and Algorithms for Offline Preference-Based Reward Learning D Shin, AD Dragan, DS Brown 🏆 🛡 Transactions on Machine Learning Research (TMLR), 2023 | 111* | 2023 |
| Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications DS Brown, S Niekum 🛡 ✋ AAAI Conference on Artificial Intelligence 33 (01), 7749-7758, 2019 | 108 | 2019 |
| Risk-aware active inverse reinforcement learning DS Brown, Y Cui, S Niekum 🏆 🛡 Conference on Robot Learning, 362-372, 2018 | 92 | 2018 |
| Causal Confusion and Reward Misidentification in Preference-Based Reward Learning J Tien, JZY He, Z Erickson, A Dragan, DS Brown 🛡🏆 International Conference on Learning Representations (ICLR), 2023 | 88* | 2023 |
| Lazydagger: Reducing context switching in interactive imitation learning R Hoque, A Balakrishna, C Putterman, M Luo, DS Brown, D Seita, ... 🤖✋ 2021 IEEE 17th International Conference on Automation Science and …, 2021 | 72 | 2021 |
| Value alignment verification DS Brown, J Schneider, A Dragan, S Niekum 🛡 International Conference on Machine Learning (ICML), 1105-1115, 2021 | 63 | 2021 |
| Efficient probabilistic performance bounds for inverse reinforcement learning D Brown, S Niekum 🏆 🛡 AAAI Conference on Artificial Intelligence 32 (1), 2018 | 62 | 2018 |
| Bayesian robust optimization for imitation learning D Brown, S Niekum, M Petrik 🛡 Advances in Neural Information Processing Systems (NeurIPS) 33, 2479-2491, 2020 | 59 | 2020 |
| Human-swarm interactions based on managing attractors DS Brown, SC Kerman, MA Goodrich ✋🐜 ACM/IEEE International Conference on Human-Robot Interaction (HRI), 90-97, 2014 | 54 | 2014 |
| Limited bandwidth recognition of collective behaviors in bio-inspired swarms DS Brown, MA Goodrich 🐜✋ International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2014 | 53 | 2014 |
| The Effect of Modeling Human Rationality Level on Learning Rewards from Multiple Feedback Types GR Ghosal, M Zurek, DS Brown, AD Dragan ✋🏆 AAAI Conference on Artificial Intelligence, 2023 | 52 | 2023 |
| Two Invariants of Human-Swarm Interaction DS Brown, MA Goodrich, SY Jung, S Kerman ✋🐜 Journal of Human-Robot Interaction 1 (1), 78-95, 2016 | 48 | 2016 |
| Situational confidence assistance for lifelong shared autonomy M Zurek, A Bobu, DS Brown, AD Dragan ✋🤖 2021 IEEE International Conference on Robotics and Automation (ICRA …, 2021 | 44 | 2021 |
| Discovery and Exploration of Novel Swarm Behaviors given Limited Robot Capabilities DS Brown, R Turner, O Hennigh, S Loscalzo 🐜 13th International Symposium on Distributed Autonomous Robotic Systems, 2016 | 41 | 2016 |
| Supporting human interaction with robust robot swarms S Kerman, D Brown, MA Goodrich 🐜✋ International Symposium on Resilient Control Systems, 197-202, 2012 | 40 | 2012 |
| Learning Representations that Enable Generalization in Assistive Tasks JZY He, Z Erickson, DS Brown, A Raghunathan, A Dragan 🤖 ✋Conference on Robot Learning (CoRL), 2022 | 39 | 2022 |
Scott NiekumAssociate Professor, University of Massachusetts AmherstVerified email at cs.umass.edu
