Junyin Ye

According to our database, Junyin Ye authored at least 8 papers between 2023 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

WHALE: Towards Generalizable and Scalable World Models for Embodied Decision-making.

Zhilong Zhang, Ruifeng Chen, Junyin Ye, Yihao Sun, Pengyuan Wang, Jingcheng Pang, Kaiyuan Li, Tianshuo Liu, Haoxin Lin, Yang Yu, Zhi-Hua Zhou

CoRR, 2024

Any-step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning.

Haoxin Lin, Yu-Yan Xu, Yihao Sun, Zhilong Zhang, Yi-Chen Li, Chengxing Jia, Junyin Ye, Jiaji Zhang, Yang Yu

CoRR, 2024

Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration.

Xiong-Hui Chen, Junyin Ye, Hang Zhao, Yi-Chen Li, XuHui Liu, Haoran Shi, Yu-Yan Xu, Zhihao Ye, Si-Hang Yang, Yang Yu, Anqi Huang, Kai Xu, Zongzhang Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Limited Preference Aided Imitation Learning from Imperfect Demonstrations.

Xingchen Cao, Fan-Ming Luo, Junyin Ye, Tian Xu, Zhilong Zhang, Yang Yu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation.

Zhilong Zhang, Yihao Sun, Junyin Ye, Tian-Shuo Liu, Jiaji Zhang, Yang Yu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Episodic Return Decomposition by Difference of Implicitly Assigned Sub-trajectory Reward.

Haoxin Lin, Hongqiu Wu, Jiaji Zhang, Yihao Sun, Junyin Ye, Yang Yu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Imitator Learning: Achieve Out-of-the-Box Imitation Ability in Variable Environments.

Xiong-Hui Chen, Junyin Ye, Hang Zhao, Yi-Chen Li, Haoran Shi, Yu-Yan Xu, Zhihao Ye, Si-Hang Yang, Anqi Huang, Kai Xu, Zongzhang Zhang, Yang Yu

CoRR, 2023

Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning.

Yihao Sun, Jiaji Zhang, Chengxing Jia, Haoxin Lin, Junyin Ye, Yang Yu

Proceedings of the International Conference on Machine Learning, 2023