Zhepeng Cen

According to our database, Zhepeng Cen authored at least 16 papers between 2019 and 2024.

Collaborative distances:

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

2024

Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens.

Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor

CoRR, 2024

OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning.

Yihang Yao, Zhepeng Cen, Wenhao Ding, Haohong Lin, Shiqi Liu, Tingnan Zhang, Wenhao Yu, Ding Zhao

CoRR, 2024

Gradient shaping for multi-constraint safe reinforcement learning.

Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Feasibility Consistent Representation Learning for Safe Reinforcement Learning.

Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao

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

Learning from Sparse Offline Datasets via Conservative Density Estimation.

Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Datasets and Benchmarks for Offline Safe Reinforcement Learning.

Zuxin Liu, Zijian Guo, Haohong Lin, Yihang Yao, Jiacheng Zhu, Zhepeng Cen, Hanjiang Hu, Wenhao Yu, Tingnan Zhang, Jie Tan, Ding Zhao

CoRR, 2023

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning.

Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Constrained Decision Transformer for Offline Safe Reinforcement Learning.

Zuxin Liu, Zijian Guo, Yihang Yao, Zhepeng Cen, Wenhao Yu, Tingnan Zhang, Ding Zhao

Proceedings of the International Conference on Machine Learning, 2023

Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data.

Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Yihang Yao, Hanjiang Hu, Ding Zhao

Proceedings of the International Conference on Machine Learning, 2023

On the Robustness of Safe Reinforcement Learning under Observational Perturbations.

Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability.

Mengdi Xu, Zuxin Liu, Peide Huang, Wenhao Ding, Zhepeng Cen, Bo Li, Ding Zhao

CoRR, 2022

Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling.

Mansur Arief, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Henry Lam, Bo Li, Ding Zhao

CoRR, 2022

Certifiable Evaluation for Autonomous Vehicle Perception Systems using Deep Importance Sampling (Deep IS).

Mansur Arief, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Bo Li, Henry Lam, Ding Zhao

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Constrained Variational Policy Optimization for Safe Reinforcement Learning.

Zuxin Liu, Zhepeng Cen, Vladislav Isenbaev, Wei Liu, Zhiwei Steven Wu, Bo Li, Ding Zhao

Proceedings of the International Conference on Machine Learning, 2022

2020

Will this Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora.

Hancheng Cao, Mengjie Cheng, Zhepeng Cen, Daniel A. McFarland, Xiang Ren

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019

Vehicle Trajectory Prediction Using Intention-based Conditional Variational Autoencoder.

Xidong Feng, Zhepeng Cen, Jianming Hu, Yi Zhang

Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019