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ORCIDZhepeng Cen
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2020 – today
- 2024
[c11]Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao:
Learning from Sparse Offline Datasets via Conservative Density Estimation. ICLR 2024- [c10]Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao:
Feasibility Consistent Representation Learning for Safe Reinforcement Learning. ICML 2024 - [c9]Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao:
Gradient shaping for multi-constraint safe reinforcement learning. L4DC 2024: 25-39 - [i12]Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao
:
Learning from Sparse Offline Datasets via Conservative Density Estimation. CoRR abs/2401.08819 (2024) - [i11]Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao:
Feasibility Consistent Representation Learning for Safe Reinforcement Learning. CoRR abs/2405.11718 (2024) - [i10]Yihang Yao, Zhepeng Cen, Wenhao Ding, Haohong Lin, Shiqi Liu, Tingnan Zhang, Wenhao Yu, Ding Zhao:
OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning. CoRR abs/2407.14653 (2024) - 2023
- [c8]Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao:
On the Robustness of Safe Reinforcement Learning under Observational Perturbations. ICLR 2023 - [c7]Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Yihang Yao, Hanjiang Hu, Ding Zhao:
Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data. ICML 2023: 21586-21610 - [c6]Zuxin Liu, Zijian Guo, Yihang Yao, Zhepeng Cen, Wenhao Yu, Tingnan Zhang, Ding Zhao:
Constrained Decision Transformer for Offline Safe Reinforcement Learning. ICML 2023: 21611-21630 - [c5]Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao:
Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning. NeurIPS 2023 - [i9]Zuxin Liu, Zijian Guo, Yihang Yao, Zhepeng Cen, Wenhao Yu, Tingnan Zhang, Ding Zhao:
Constrained Decision Transformer for Offline Safe Reinforcement Learning. CoRR abs/2302.07351 (2023) - [i8]Zuxin Liu, Zijian Guo, Haohong Lin, Yihang Yao, Jiacheng Zhu, Zhepeng Cen, Hanjiang Hu, Wenhao Yu, Tingnan Zhang, Jie Tan, Ding Zhao:
Datasets and Benchmarks for Offline Safe Reinforcement Learning. CoRR abs/2306.09303 (2023) - [i7]Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao:
Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning. CoRR abs/2310.03718 (2023) - [i6]Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao:
Gradient Shaping for Multi-Constraint Safe Reinforcement Learning. CoRR abs/2312.15127 (2023) - 2022
- [c4]Zuxin Liu, Zhepeng Cen, Vladislav Isenbaev, Wei Liu, Zhiwei Steven Wu, Bo Li, Ding Zhao:
Constrained Variational Policy Optimization for Safe Reinforcement Learning. ICML 2022: 13644-13668 - [c3]Mansur Arief, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Bo Li, Henry Lam, Ding Zhao:
Certifiable Evaluation for Autonomous Vehicle Perception Systems using Deep Importance Sampling (Deep IS). ITSC 2022: 1736-1742 - [i5]Zuxin Liu, Zhepeng Cen, Vladislav Isenbaev, Wei Liu, Zhiwei Steven Wu, Bo Li, Ding Zhao:
Constrained Variational Policy Optimization for Safe Reinforcement Learning. CoRR abs/2201.11927 (2022) - [i4]Mansur Arief, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Henry Lam, Bo Li, Ding Zhao:
Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling. CoRR abs/2204.02351 (2022) - [i3]Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao:
On the Robustness of Safe Reinforcement Learning under Observational Perturbations. CoRR abs/2205.14691 (2022) - [i2]Mengdi Xu, Zuxin Liu, Peide Huang, Wenhao Ding, Zhepeng Cen, Bo Li, Ding Zhao:
Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability. CoRR abs/2209.08025 (2022) - 2020
- [c2]Hancheng Cao, Mengjie Cheng, Zhepeng Cen, Daniel A. McFarland, Xiang Ren:
Will this Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora. EMNLP (Findings) 2020: 1746-1757 - [i1]Hancheng Cao, Mengjie Cheng, Zhepeng Cen, Daniel A. McFarland, Xiang Ren:
Will This Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora. CoRR abs/2010.06657 (2020)
2010 – 2019
- 2019
- [c1]Xidong Feng, Zhepeng Cen, Jianming Hu, Yi Zhang:
Vehicle Trajectory Prediction Using Intention-based Conditional Variational Autoencoder. ITSC 2019: 3514-3519
Coauthor Index
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