| Cooperative multi-agent control using deep reinforcement learning JK Gupta, M Egorov, M Kochenderfer Autonomous Agents and Multiagent Systems: AAMAS 2017 Workshops, Best Papers …, 2017 | 966 | 2017 |
| Model-Free Imitation Learning with Policy Optimization J Ho, JK Gupta, S Ermon International Conference on Machine Learning, 2016, 2016 | 151 | 2016 |
| POMDPs.jl: A Framework for Sequential Decision Making under Uncertainty M Egorov, ZN Sunberg, E Balaban, TA Wheeler, JK Gupta, ... Journal of Machine Learning Research 18 (26), 1-5, 2017 | 143 | 2017 |
| Learning policy representations in multiagent systems A Grover, M Al-Shedivat, J Gupta, Y Burda, H Edwards International conference on machine learning, 1802-1811, 2018 | 113 | 2018 |
| Deep implicit coordination graphs for multi-agent reinforcement learning S Li, JK Gupta, P Morales, R Allen, MJ Kochenderfer arXiv preprint arXiv:2006.11438, 2020 | 65 | 2020 |
| Dynamic multi-robot task allocation under uncertainty and temporal constraints S Choudhury, JK Gupta, MJ Kochenderfer, D Sadigh, J Bohg Autonomous Robots 46 (1), 231-247, 2022 | 62 | 2022 |
| Simulating Emergent Properties of Human Driving Behavior Using Multi-Agent Reward Augmented Imitation Learning RP Bhattacharyya, DJ Phillips, C Liu, JK Gupta, K Driggs-Campbell, ... International Conference on Robotics and Automation, 2019 | 57 | 2019 |
| ClimaX: A foundation model for weather and climate T Nguyen, J Brandstetter, A Kapoor, JK Gupta, A Grover arXiv preprint arXiv:2301.10343, 2023 | 53 | 2023 |
| Structured mechanical models for robot learning and control JK Gupta, K Menda, Z Manchester, M Kochenderfer Learning for Dynamics and Control, 328-337, 2020 | 38 | 2020 |
| Planit: A crowdsourcing approach for learning to plan paths from large scale preference feedback A Jain, D Das, JK Gupta, A Saxena 2015 IEEE International Conference on Robotics and Automation (ICRA), 877-884, 2015 | 36 | 2015 |
| Model primitives for hierarchical lifelong reinforcement learning B Wu, JK Gupta, M Kochenderfer Autonomous Agents and Multi-Agent Systems 34, 1-38, 2020 | 35 | 2020 |
| Clifford neural layers for PDE modeling J Brandstetter, R Berg, M Welling, JK Gupta arXiv preprint arXiv:2209.04934, 2022 | 32 | 2022 |
| A general framework for structured learning of mechanical systems JK Gupta, K Menda, Z Manchester, MJ Kochenderfer arXiv preprint arXiv:1902.08705, 2019 | 32 | 2019 |
| Mtba: Matlab toolbox for biclustering analysis JK Gupta, S Singh, NK Verma IEEE workshop on computational intelligence: theories, applications and …, 2013 | 27* | 2013 |
| Smartphone application for fault recognition NK Verma, S Singh, JK Gupta, RK Sevakula, S Dixit, A Salour 2012 Sixth International Conference on Sensing Technology (ICST), 1-6, 2012 | 26 | 2012 |
| Towards multi-spatiotemporal-scale generalized pde modeling JK Gupta, J Brandstetter arXiv preprint arXiv:2209.15616, 2022 | 24 | 2022 |
| Scalable anytime planning for multi-agent mdps S Choudhury, JK Gupta, P Morales, MJ Kochenderfer arXiv preprint arXiv:2101.04788, 2021 | 15 | 2021 |
| Normalizing Flow Policies for Multi-agent Systems X Ma, JK Gupta, MJ Kochenderfer International Conference on Decision and Game Theory for Security, 2020 | 12 | 2020 |
| Geometric clifford algebra networks D Ruhe, JK Gupta, S De Keninck, M Welling, J Brandstetter arXiv preprint arXiv:2302.06594, 2023 | 11 | 2023 |
| Evaluating generalization in multiagent systems using agent-interaction graphs A Grover, M Al-Shedivat, JK Gupta, Y Burda, H Edwards Proceedings of the 17th International Conference on Autonomous Agents and …, 2018 | 11 | 2018 |
Mykel J. KochenderferAssociate Professor, Stanford University在 stanford.edu 的电子邮件经过验证
