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Jiafei Lyu
Jiafei Lyu
PhD of Control Science and Engineering, Tsinghua Shenzhen International Graduate School
Verified email at mails.tsinghua.edu.cn - Homepage
Title
Cited by
Cited by
Year
Mildly conservative Q-learning for offline reinforcement learning
J Lyu, X Ma, X Li, Z Lu
NeurIPS 2022 (Spotlight), 2022
532022
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
412020
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
342021
Double Check Your State Before Trusting It: Confidence-Aware Bidirectional Offline Model-Based Imagination
J Lyu, X Li, Z Lu
NeurIPS 2022 (Spotlight), 2022
122022
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
7*2021
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
52023
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
32022
Value Activation for Bias Alleviation: Generalized-activated Deep Double Deterministic Policy Gradients
J Lyu, Y Yang, J Yan, X Li
Neurocomputing, 2021
32021
Zero-shot Preference Learning for Offline RL via Optimal Transport
R Liu, Y Du, F Bai, J Lyu, X Li
Optimal Transport and Machine Learning Workshop@NeurIPS 2023, 2023
22023
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
22023
Exploration and Anti-Exploration with Distributional Random Network Distillation
K Yang, J Tao, J Lyu, X Li
arXiv preprint arXiv:2401.09750, 2024
12024
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
12023
The primacy bias in Model-based RL
Z Qiao, J Lyu, X Li
arXiv preprint arXiv:2310.15017, 2023
12023
Multi-Step Hindsight Experience Replay with Bias Reduction for Efficient Multi-Goal Reinforcement Learning
Y Yang, R Yang, J Lyu, J Yan, F Luo, D Luo, X Li, L Li
2023 International Conference on Frontiers of Robotics and Software …, 2023
12023
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
12023
Uncertainty-driven trajectory truncation for data augmentation in offline reinforcement learning
J Zhang, J Lyu, X Ma, J Yan, J Yang, L Wan, X Li
ECAI 2023, 3018-3025, 2023
12023
PRAG: Periodic Regularized Action Gradient for Efficient Continuous Control
X Li, Z Qiao, A Gong, J Lyu, C Yu, J Yan, X Li
Pacific Rim International Conference on Artificial Intelligence, 106-119, 2022
12022
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
2024
Understanding What Affects Generalization Gap in Visual Reinforcement Learning: Theory and Empirical Evidence
J Lyu, L Wan, X Li, Z Lu
arXiv preprint arXiv:2402.02701, 2024
2024
Zero-shot Cross-task Preference Alignment for Offline RL via Optimal Transport
R Liu, Y Du, F Bai, J Lyu, X Li
2023
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Articles 1–20