| Mildly conservative Q-learning for offline reinforcement learning J Lyu, X Ma, X Li, Z Lu NeurIPS 2022 (Spotlight), 2022 | 130 | 2022 |
| Nuclear power plants with artificial intelligence in industry 4.0 era: Top-level design and current applications—A systemic review C Lu, J Lyu, L Zhang, A Gong, Y Fan, J Yan, X Li IEEE Access 8, 194315-194332, 2020 | 77 | 2020 |
| Efficient Continuous Control with Double Actors and Regularized Critics J Lyu, X Ma, J Yan, X Li In proceedings of 36th AAAI Conference on Artificial Intelligence (AAAI-22 oral), 2021 | 61 | 2021 |
| Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model K Yang, J Tao, J Lyu, C Ge, J Chen, Q Li, W Shen, X Zhu, X Li IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024), 2023 | 47 | 2023 |
| Double Check Your State Before Trusting It: Confidence-Aware Bidirectional Offline Model-Based Imagination J Lyu, X Li, Z Lu NeurIPS 2022 (Spotlight), 2022 | 24 | 2022 |
| Uncertainty-driven Trajectory Truncation for Model-based Offline Reinforcement Learning J Zhang, J Lyu, X Ma, J Yan, J Yang, L Wan, X Li ECAI 2023 (Oral); ICRA 2023 L-DOD Workshop, 2023 | 22* | 2023 |
| Exploration and Anti-Exploration with Distributional Random Network Distillation K Yang, J Tao, J Lyu, X Li International Conference on Machine Learning (ICML 2024), 2024 | 11 | 2024 |
| Off-Policy RL Algorithms Can be Sample-Efficient for Continuous Control via Sample Multiple Reuse J Lyu, L Wan, Z Lu, X Li Information Sciences, 2023 | 11 | 2023 |
| Bias-reduced multi-step hindsight experience replay for efficient multi-goal reinforcement learning R Yang, J Lyu, Y Yang, J Yan, F Luo, D Luo, L Li, X Li arXiv preprint arXiv:2102.12962, 2021 | 11* | 2021 |
| Normalization Enhances Generalization in Visual Reinforcement Learning L Li, J Lyu, G Ma, Z Wang, Z Yang, X Li, Z Li AAMAS 2024 (Oral); Generalization in Planning Workshop@NeurIPS 2023, 2023 | 10 | 2023 |
| Value Activation for Bias Alleviation: Generalized-activated Deep Double Deterministic Policy Gradients J Lyu, Y Yang, J Yan, X Li Neurocomputing, 2021 | 9 | 2021 |
| PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation R Liu, Y Du, F Bai, J Lyu, X Li International Conference on Machine Learning (ICML 2024), 2024 | 7* | 2024 |
| SEABO: A Simple Search-Based Method for Offline Imitation Learning J Lyu, X Ma, L Wan, R Liu, X Li, Z Lu International Conference on Learning Representations (ICLR 2024), 2024 | 6 | 2024 |
| Mind the Model, Not the Agent: The Primacy Bias in Model-based RL Z Qiao, J Lyu, X Li arXiv preprint arXiv:2310.15017, 2023 | 5* | 2023 |
| State Advantage Weighting for Offline RL J Lyu, A Gong, L Wan, Z Lu, X Li ICLR2023 tiny paper; 3rd Offline Reinforcement Learning Workshop at NeurIPS 2022, 2022 | 5 | 2022 |
| aicheng Gong, Le Wan, Zongqing Lu, and Xiu Li. State advantage weighting for offline RL J Lyu 3rd Offline RL Workshop: Offline RL as a” Launchpad, 2022 | 5 | 2022 |
| A two-stage reinforcement learning-based approach for multi-entity task allocation A Gong, K Yang, J Lyu, X Li Engineering Applications of Artificial Intelligence 136, 108906, 2024 | 4 | 2024 |
| Cross-Domain Policy Adaptation by Capturing Representation Mismatch J Lyu, C Bai, J Yang, Z Lu, X Li International Conference on Machine Learning (ICML 2024), 2024 | 4 | 2024 |
| Understanding what affects generalization gap in visual reinforcement learning: Theory and empirical evidence J Lyu, L Wan, X Li, Z Lu Journal of Artificial Intelligence Research, 2024 | 4 | 2024 |
| A Large Language Model-Driven Reward Design Framework via Dynamic Feedback for Reinforcement Learning S Sun, R Liu, J Lyu, JW Yang, L Zhang, X Li arXiv preprint arXiv:2410.14660, 2024 | 3 | 2024 |
Xiu LITsinghua UniversityPotvrđena adresa e-pošte na sz.tsinghua.edu.cn
