| Learning sampling distributions for robot motion planning B Ichter, J Harrison, M Pavone International Conference on Robotics and Automation (ICRA), 2018 | 418 | 2018 |
| Network offloading policies for cloud robotics: a learning-based approach S Chinchali, A Sharma, J Harrison, A Elhafsi, D Kang, E Pergament, ... Robotics: Science and Systems (RSS), 2019 | 135 | 2019 |
| Meta-learning priors for efficient online bayesian regression J Harrison, A Sharma, M Pavone Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018 | 121 | 2018 |
| Deep Reinforcement Learning amidst Continual Structured Non-Stationarity A Xie, J Harrison, C Finn International Conference on Machine Learning (ICML), 2021 | 110* | 2021 |
| Continuous meta-learning without tasks J Harrison, A Sharma, C Finn, M Pavone Neural Information Processing Systems (NeurIPS), 2020 | 96 | 2020 |
| Safe Active Dynamics Learning and Control: A Sequential Exploration-Exploitation Framework T Lew, A Sharma, J Harrison, A Bylard, M Pavone Transactions on Robotics (TRO), 2022 | 76* | 2022 |
| BaRC: Backward reachability curriculum for robotic reinforcement learning B Ivanovic, J Harrison, A Sharma, M Chen, M Pavone International Conference on Robotics and Automation (ICRA), 2019 | 74 | 2019 |
| Velo: Training versatile learned optimizers by scaling up L Metz, J Harrison, CD Freeman, A Merchant, L Beyer, J Bradbury, ... arXiv preprint arXiv:2211.09760, 2022 | 70 | 2022 |
| General-purpose in-context learning by meta-learning transformers L Kirsch, J Harrison, J Sohl-Dickstein, L Metz arXiv preprint arXiv:2212.04458, 2022 | 67 | 2022 |
| Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems D Gammelli, K Yang, J Harrison, F Rodrigues, FC Pereira, M Pavone Conference on Decision and Control (CDC), 2021 | 65 | 2021 |
| Beyond human data: Scaling self-training for problem-solving with language models A Singh, JD Co-Reyes, R Agarwal, A Anand, P Patil, PJ Liu, J Harrison, ... Transactions on Machine Learning Research (TMLR), 2024 | 62 | 2024 |
| Nanoindentation studies to separate thermal and optical effects in photo-softening of azo polymers JM Harrison, D Goldbaum, TC Corkery, CJ Barrett, RR Chromik Journal of Materials Chemistry C 3 (5), 995-1003, 2015 | 46 | 2015 |
| Control adaptation via meta-learning dynamics J Harrison, A Sharma, R Calandra, M Pavone Workshop on Meta-Learning at NeurIPS 2018, 2018 | 38 | 2018 |
| Adapt: zero-shot adaptive policy transfer for stochastic dynamical systems J Harrison, A Garg, B Ivanovic, Y Zhu, S Savarese, L Fei-Fei, M Pavone International Symposium on Robotics Research (ISRR), 2017 | 32 | 2017 |
| Practical tradeoffs between memory, compute, and performance in learned optimizers L Metz, CD Freeman, J Harrison, N Maheswaranathan, J Sohl-Dickstein Conference on Lifelong Learning Agents (CoLLAs), 2022 | 30 | 2022 |
| Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty R Sinha, J Harrison, SM Richards, M Pavone American Control Conference (ACC), 2022 | 29 | 2022 |
| Expanding the deployment envelope of behavior prediction via adaptive meta-learning B Ivanovic, J Harrison, M Pavone International Conference on Robotics and Automation (ICRA), 2023 | 28 | 2023 |
| Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand D Gammelli, K Yang, J Harrison, F Rodrigues, FC Pereira, M Pavone Conference on Knowledge Discovery and Data Mining (KDD), 2022 | 23 | 2022 |
| Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems T Enders, J Harrison, M Pavone, M Schiffer Learning for Dynamics and Control (L4DC), 2023 | 20 | 2023 |
| A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases J Harrison, L Metz, J Sohl-Dickstein Neural Information Processing Systems (NeurIPS), 2022 | 19 | 2022 |