| Self6d: Self-supervised monocular 6d object pose estimation G Wang, F Manhardt, J Shao, X Ji, N Navab, F Tombari Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 121 | 2020 |
| Pfrl: Pose-free reinforcement learning for 6d pose estimation J Shao, Y Jiang, G Wang, Z Li, X Ji Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 34 | 2020 |
| Wasserstein unsupervised reinforcement learning S He, Y Jiang, H Zhang, J Shao, X Ji Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6884-6892, 2022 | 14 | 2022 |
| Self-organized group for cooperative multi-agent reinforcement learning J Shao, Z Lou, H Zhang, Y Jiang, S He, X Ji Advances in Neural Information Processing Systems 35, 5711-5723, 2022 | 11 | 2022 |
| State deviation correction for offline reinforcement learning H Zhang, J Shao, Y Jiang, S He, G Zhang, X Ji Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 9022-9030, 2022 | 9 | 2022 |
| Credit assignment with meta-policy gradient for multi-agent reinforcement learning J Shao, H Zhang, Y Jiang, S He, X Ji arXiv preprint arXiv:2102.12957, 2021 | 8 | 2021 |
| Reducing conservativeness oriented offline reinforcement learning H Zhang, J Shao, Y Jiang, S He, X Ji arXiv preprint arXiv:2103.00098, 2021 | 6 | 2021 |
| Skill discovery of coordination in multi-agent reinforcement learning S He, J Shao, X Ji arXiv preprint arXiv:2006.04021, 2020 | 6 | 2020 |
| Optimizing the dynamic treatment regime of in-hospital warfarin anticoagulation in patients after surgical valve replacement using reinforcement learning J Zeng, J Shao, S Lin, H Zhang, X Su, X Lian, Y Zhao, X Ji, Z Zheng Journal of the American Medical Informatics Association 29 (10), 1722-1732, 2022 | 5 | 2022 |
| Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement Learning J Shao, Y Qu, C Chen, H Zhang, X Ji Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
| Complementary attention for multi-agent reinforcement learning J Shao, H Zhang, Y Qu, C Liu, S He, Y Jiang, X Ji International Conference on Machine Learning, 30776-30793, 2023 | 2 | 2023 |
| Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks Y Qu, B Wang, J Shao, Y Jiang, C Chen, Z Ye, L Linc, Y Feng, L Lai, H Qin, ... Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| DARL: distance-aware uncertainty estimation for offline reinforcement learning H Zhang, J Shao, S He, Y Jiang, X Ji Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 11210 …, 2023 | 1 | 2023 |
| SPD: Synergy Pattern Diversifying Oriented Unsupervised Multi-agent Reinforcement Learning Y Jiang, J Shao, S He, H Zhang, X Ji Advances in Neural Information Processing Systems 35, 20661-20674, 2022 | 1 | 2022 |
| HoK3v3: an Environment for Generalization in Heterogeneous Multi-agent Reinforcement Learning L Liu, J Shao, X Chen, Y Qu, B Wang, Z Ye, Y Tu, H Qin, YJ Feng, L Lai, ... | | 2023 |
| Reinforcement learning-based label-free six-dimensional object pose prediction method and apparatus X Ji, S Jianzhun US Patent App. 17/881,615, 2023 | | 2023 |
| Pessimistic Policy Iteration for Offline Reinforcement Learning H Zhang, B Wang, Y Mao, J Shao, Y Jiang, Y Xu, X Ji | | 2022 |
| Unsupervised Data Generation for Offline Reinforcement Learning: A Perspective from Model S He, H Zhang, J Shao, Y Jiang, X Ji | | |
