| Embodiedgpt: Vision-language pre-training via embodied chain of thought Y Mu, Q Zhang, M Hu, W Wang, M Ding, J Jin, B Wang, J Dai, Y Qiao, ... Advances in Neural Information Processing Systems 36, 2024 | 198 | 2024 |
| Mapless navigation among dynamics with social-safety-awareness: a reinforcement learning approach from 2d laser scans J Jin, NM Nguyen, N Sakib, D Graves, H Yao, M Jagersand 2020 IEEE international conference on robotics and automation (ICRA), 6979-6985, 2020 | 77 | 2020 |
| Online object and task learning via human robot interaction M Dehghan, Z Zhang, M Siam, J Jin, L Petrich, M Jagersand 2019 international conference on robotics and automation (ICRA), 2132-2138, 2019 | 35 | 2019 |
| A quantitative analysis of activities of daily living: Insights into improving functional independence with assistive robotics L Petrich, J Jin, M Dehghan, M Jagersand 2022 International Conference on Robotics and Automation (ICRA), 6999-7006, 2022 | 31* | 2022 |
| A Geometric Perspective on Visual Imitation Learning J Jin, L Petrich, M Dehghan, M Jagersand 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020 | 21 | 2020 |
| Learning robust driving policies without online exploration D Graves, NM Nguyen, K Hassanzadeh, J Jin, J Luo 2021 IEEE International Conference on Robotics and Automation (ICRA), 13186 …, 2021 | 20* | 2021 |
| Offline learning of counterfactual predictions for real-world robotic reinforcement learning J Jin, D Graves, C Haigh, J Luo, M Jagersand 2022 International Conference on Robotics and Automation (ICRA), 3616-3623, 2022 | 19* | 2022 |
| Robot eye-hand coordination learning by watching human demonstrations: a task function approximation approach J Jin, L Petrich, M Dehghan, Z Zhang, M Jagersand 2019 international conference on robotics and automation (ICRA), 6624-6630, 2019 | 18 | 2019 |
| Visual geometric skill inference by watching human demonstration J Jin, L Petrich, Z Zhang, M Dehghan, M Jagersand 2020 ieee international conference on robotics and automation (ICRA), 8985-8991, 2020 | 11 | 2020 |
| Replay memory as an empirical MDP: Combining conservative estimation with experience replay H Zhang, C Xiao, H Wang, J Jin, M Müller The Eleventh International Conference on Learning Representations, 2023 | 9 | 2023 |
| Dynamic Decision Frequency with Continuous Options A Karimi, J Jin, J Luo, AR Mahmood, M Jagersand, S Tosatto 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2023 | 8 | 2023 |
| A Simple Decentralized Cross-Entropy Method Z Zhang, J Jin, M Jagersand, J Luo, D Schuurmans Advances in Neural Information Processing Systems (NeurIPS), 2022 35, 36495 …, 2022 | 8 | 2022 |
| Generalizable task representation learning from human demonstration videos: a geometric approach J Jin, M Jagersand 2022 International Conference on Robotics and Automation (ICRA), 2504-2510, 2022 | 5 | 2022 |
| Long range teleoperation for fine manipulation tasks under time-delay network conditions J Jin, L Petrich, S He, M Dehghan, M Jagersand arXiv preprint arXiv:1903.09189, 2019 | 5 | 2019 |
| A generative model-based predictive display for robotic teleoperation B Xie, M Han, J Jin, M Barczyk, M Jägersand 2021 IEEE International Conference on Robotics and Automation (ICRA), 2407-2413, 2021 | 4 | 2021 |
| LaFFi: Leveraging Hybrid Natural Language Feedback for Fine-tuning Language Models Q Li, Y Cao, J Kang, T Yang, X Chen, J Jin, ME Taylor arXiv preprint arXiv:2401.00907, 2023 | 3 | 2023 |
| What makes useful auxiliary tasks in reinforcement learning: investigating the effect of the target policy B Rafiee, J Jin, J Luo, A White The 5th Multidisciplinary Conference on Reinforcement Learning and Decision …, 2022 | 3 | 2022 |
| Lispr: An options framework for policy reuse with reinforcement learning D Graves, J Jin, J Luo arXiv preprint arXiv:2012.14942, 2020 | 2 | 2020 |
| Evaluation of state representation methods in robot hand-eye coordination learning from demonstration J Jin, M Dehghan, L Petrich, SW Lu, M Jagersand arXiv preprint arXiv:1903.00634, 2019 | 2 | 2019 |
| Label-Free Adaptive Gaussian Sample Consensus Framework for Learning From Perfect and Imperfect Demonstrations Y Hu, Z Samadikhoshkho, J Jin, M Tavakoli IEEE Transactions on Medical Robotics and Bionics, 2024 | 1 | 2024 |
Martin JagersandUniversity of AlbertaVerificeret mail på cs.ualberta.ca
