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

Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees. - Guiliang Liu; Oliver Schulte; Wang Zhu 001; Qingcan Li (ECML/PKDD (2), 2018)

Interpreting Deep Sports Analytics: Valuing Actions and Players in the NHL. - Guiliang Liu; Wang Zhu 001; Oliver Schulte (MLSA@PKDD/ECML, 2018)

Cracking the Black Box: Distilling Deep Sports Analytics. - Xiangyu Sun; Jack Davis; Oliver Schulte; Guiliang Liu (KDD, 2020)

Learning Agent Representations for Ice Hockey. - Guiliang Liu; Oliver Schulte; Pascal Poupart; Mike Rudd; Mehrsan Javan (NeurIPS, 2020)

An Advantage Actor-Critic Algorithm with Confidence Exploration for Open Information Extraction. - Guiliang Liu; Xu Li 001; Mingming Sun 001; Ping Li 001 (SDM, 2020)

Extracting Knowledge from Web Text with Monte Carlo Tree Search. - Guiliang Liu; Xu Li 001; Jiakang Wang; Mingming Sun 001; Ping Li 001 (WWW, 2020)

Deep soccer analytics: learning an action-value function for evaluating soccer players. - Guiliang Liu; Yudong Luo; Oliver Schulte; Tarak Kharrat (Data Min. Knowl. Discov., 2020)

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

NTS-NOTEARS: Learning Nonparametric Temporal DAGs With Time-Series Data and Prior Knowledge. - Xiangyu Sun; Guiliang Liu; Pascal Poupart; Oliver Schulte (CoRR, 2021)

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

Distributional Reinforcement Learning with Monotonic Splines. - Yudong Luo; Guiliang Liu; Haonan Duan 002; Oliver Schulte; Pascal Poupart (ICLR, 2022)

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

NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge. - Xiangyu Sun; Oliver Schulte; Guiliang Liu; Pascal Poupart (AISTATS, 2023)

Learning Soft Constraints From Constrained Expert Demonstrations. - Ashish Gaurav; Kasra Rezaee; Guiliang Liu; Pascal Poupart (ICLR, 2023)

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

An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. - Yudong Luo; Guiliang Liu; Pascal Poupart; Yangchen Pan (NeurIPS, 2023)

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

Unimodal Training-Multimodal Prediction: Cross-modal Federated Learning with Hierarchical Aggregation. - Rongyu Zhang; Xiaowei Chi; Guiliang Liu; Wenyi Zhang; Yuan Du; Fangxin Wang 001 (CoRR, 2023)

Modelling Competitive Behaviors in Autonomous Driving Under Generative World Model. - Guanren Qiao; Guorui Quan; Rongxiao Qu; Guiliang Liu (ECCV (35), 2024)

Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning. - Sheng Xu; Guiliang Liu (ICLR, 2024)

Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation. - Guorui Quan; Zhiqiang Xu; Guiliang Liu (ICML, 2024)

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

Robust Inverse Constrained Reinforcement Learning under Model Misspecification. - Sheng Xu; Guiliang Liu (ICML, 2024)

TrafficGamer: Reliable and Flexible Traffic Simulation for Safety-Critical Scenarios with Game-Theoretic Oracles. - Guanren Qiao; Guorui Quan; Jiawei Yu; Shujun Jia; Guiliang Liu (CoRR, 2024)

Provably Efficient Exploration in Inverse Constrained Reinforcement Learning. - Bo Yue; Jian Li; Guiliang Liu (CoRR, 2024)

Offline Inverse Constrained Reinforcement Learning for Safe-Critical Decision Making in Healthcare. - Nan Fang; Guiliang Liu; Wei Gong 001 (CoRR, 2024)

Prof. Robot: Differentiable Robot Rendering Without Static and Self-Collisions. - Quanyuan Ruan; Jiabao Lei; Wenhao Yuan 007; Yanglin Zhang; Dekun Lu; Guiliang Liu; Kui Jia (CVPR, 2025)

A Distributional Approach to Uncertainty-Aware Preference Alignment Using Offline Demonstrations. - Sheng Xu; Bo Yue; Hongyuan Zha; 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 (ICLR, 2025)

Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers. - Runyi Zhao; Sheng Xu; Bo Yue; Guiliang Liu (ICLR, 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 (Trans. Mach. Learn. Res., 2025)

You Only Teach Once: Learn One-Shot Bimanual Robotic Manipulation from Video Demonstrations. - Huayi Zhou 001; Ruixiang Wang; Yunxin Tai; Yueci Deng; Guiliang Liu; Kui Jia (CoRR, 2025)

HWC-Loco: A Hierarchical Whole-Body Control Approach to Robust Humanoid Locomotion. - Sixu Lin; Guanren Qiao; Yunxin Tai; Ang Li; Kui Jia; Guiliang Liu (CoRR, 2025)

GAT-Grasp: Gesture-Driven Affordance Transfer for Task-Aware Robotic Grasping. - Ruixiang Wang; Huayi Zhou 001; Xinyue Yao; Guiliang Liu; Kui Jia (CoRR, 2025)

Real-Time Verification of Embodied Reasoning for Generative Skill Acquisition. - Bo Yue; Shuqi Guo; Kaiyu Hu; Chujiao Wang; Benyou Wang; Kui Jia; Guiliang Liu (CoRR, 2025)

SignBot: Learning Human-to-Humanoid Sign Language Interaction. - Guanren Qiao; Sixu Lin; Ronglai Zuo Zhizheng Wu; Kui Jia; Guiliang Liu (CoRR, 2025)