Guiliang Liu

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 27

Top Topics

Object Representation

Reinforcement Learning

Bayesian Nonparametric

Soft Constraints

Top Venues

Publications

Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart
Confidence Aware Inverse Constrained Reinforcement Learning. CoRR (2024)
Sheng Xu, Guiliang Liu
Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning. ICLR (2024)
Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. NeurIPS (2023)
Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart
Learning Soft Constraints From Constrained Expert Demonstrations. ICLR (2023)
Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge. AISTATS (2023)
Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. CoRR (2023)
Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart
Benchmarking Constraint Inference in Inverse Reinforcement Learning. ICLR (2023)
Guanren Qiao, Guiliang Liu, Pascal Poupart, Zhiqiang Xu
Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations. NeurIPS (2023)
Rongyu Zhang, Xiaowei Chi, Guiliang Liu, Wenyi Zhang, Yuan Du, Fangxin Wang
Unimodal Training-Multimodal Prediction: Cross-modal Federated Learning with Hierarchical Aggregation. CoRR (2023)
Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart
Distributional Reinforcement Learning with Monotonic Splines. ICLR (2022)
Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart
Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game. NeurIPS (2022)
Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart
Learning Soft Constraints From Constrained Expert Demonstrations. CoRR (2022)
Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart
Benchmarking Constraint Inference in Inverse Reinforcement Learning. CoRR (2022)
Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart
Learning Object-Oriented Dynamics for Planning from Text. ICLR (2022)
Xiangyu Sun, Guiliang Liu, Pascal Poupart, Oliver Schulte
NTS-NOTEARS: Learning Nonparametric Temporal DAGs With Time-Series Data and Prior Knowledge. CoRR (2021)
Guiliang Liu, Xiangyu Sun, Oliver Schulte, Pascal Poupart
Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning. NeurIPS (2021)
Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu
Cracking the Black Box: Distilling Deep Sports Analytics. CoRR (2020)
Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu
Cracking the Black Box: Distilling Deep Sports Analytics. KDD (2020)
Guiliang Liu, Xu Li, Jiakang Wang, Mingming Sun, Ping Li
Extracting Knowledge from Web Text with Monte Carlo Tree Search. WWW (2020)
Guiliang Liu, Oliver Schulte, Pascal Poupart, Mike Rudd, Mehrsan Javan
Learning Agent Representations for Ice Hockey. NeurIPS (2020)
Guiliang Liu, Yudong Luo, Oliver Schulte, Tarak Kharrat
Deep soccer analytics: learning an action-value function for evaluating soccer players. Data Min. Knowl. Discov. 34 (5) (2020)
Guiliang Liu, Xu Li, Mingming Sun, Ping Li
An Advantage Actor-Critic Algorithm with Confidence Exploration for Open Information Extraction. SDM (2020)
Guiliang Liu, Oliver Schulte
Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation. IJCAI (2018)
Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees. ECML/PKDD (2) (2018)
Guiliang Liu, Oliver Schulte
Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation. CoRR (2018)
Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees. CoRR (2018)
Guiliang Liu, Wang Zhu, Oliver Schulte
Interpreting Deep Sports Analytics: Valuing Actions and Players in the NHL. MLSA@PKDD/ECML (2018)