Liu, Guiliang

26 publications

TMLR 2025 A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges Guiliang Liu, Sheng Xu, Shicheng Liu, Ashish Gaurav, Sriram Ganapathi Subramanian, Pascal Poupart

ICLR 2025 A Distributional Approach to Uncertainty-Aware Preference Alignment Using Offline Demonstrations Sheng Xu, Bo Yue, Hongyuan Zha, Guiliang Liu

ICML 2025 DexScale: Automating Data Scaling for Sim2Real Generalizable Robot Control Guiliang Liu, Yueci Deng, Runyi Zhao, Huayi Zhou, Jian Chen, Jietao Chen, Ruiyan Xu, Yunxin Tai, Kui Jia

CVPR 2025 Prof. Robot: Differentiable Robot Rendering Without Static and Self-Collisions Quanyuan Ruan, Jiabao Lei, Wenhao Yuan, Yanglin Zhang, Dekun Lu, Guiliang Liu, Kui Jia

ICML 2025 Provably Efficient Exploration in Inverse Constrained Reinforcement Learning Bo Yue, Jian Li, Guiliang Liu

ICLR 2025 Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers Runyi Zhao, Sheng Xu, Bo Yue, Guiliang Liu

NeurIPS 2025 Uncertainty-Aware Preference Alignment for Diffusion Policies Runqing Miao, Sheng Xu, Runyi Zhao, Wai Kin Victor Chan, Guiliang Liu

ICLR 2025 Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning Bo Yue, Shufan Wang, Ashish Gaurav, Jian Li, Pascal Poupart, Guiliang Liu

ICML 2024 Confidence Aware Inverse Constrained Reinforcement Learning Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart

ICML 2024 Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation Guorui Quan, Zhiqiang Xu, Guiliang Liu

ECCV 2024 Modelling Competitive Behaviors in Autonomous Driving Under Generative World Model Guanren Qiao, Guiliang Liu, Guorui Quan, Rongxiao Qu

ICML 2024 Robust Inverse Constrained Reinforcement Learning Under Model Misspecification Sheng Xu, Guiliang Liu

ICLR 2024 Uncertainty-Aware Constraint Inference in Inverse Constrained Reinforcement Learning Sheng Xu, Guiliang Liu

ICMLW 2024 Uncertainty-Aware Preference Alignment in Reinforcement Learning from Human Feedback Sheng Xu, Bo Yue, Hongyuan Zha, Guiliang Liu

NeurIPS 2023 An Alternative to Variance: Gini Deviation for Risk-Averse Policy Gradient Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan

ICLR 2023 Benchmarking Constraint Inference in Inverse Reinforcement Learning Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart

ICLR 2023 Learning Soft Constraints from Constrained Expert Demonstrations Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart

NeurIPS 2023 Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations Guanren Qiao, Guiliang Liu, Pascal Poupart, Zhiqiang Xu

AISTATS 2023 NTS-NOTEARS: Learning Nonparametric DBNs with Prior Knowledge Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart

ICLR 2022 Distributional Reinforcement Learning with Monotonic Splines Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart

ICLR 2022 Learning Object-Oriented Dynamics for Planning from Text Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart

NeurIPS 2022 Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart

NeurIPS 2021 Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning Guiliang Liu, Xiangyu Sun, Oliver Schulte, Pascal Poupart

NeurIPS 2020 Learning Agent Representations for Ice Hockey Guiliang Liu, Oliver Schulte, Pascal Poupart, Mike Rudd, Mehrsan Javan

IJCAI 2018 Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation Guiliang Liu, Oliver Schulte

ECML-PKDD 2018 Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li