Guiliang Liu

According to our database, Guiliang Liu authored at least 28 papers between 2018 and 2024.

Collaborative distances:

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

2024

Offline Inverse Constrained Reinforcement Learning for Safe-Critical Decision Making in Healthcare.

Nan Fang, Guiliang Liu, Wei Gong

CoRR, 2024

Provably Efficient Exploration in Inverse Constrained Reinforcement Learning.

Bo Yue, Jian Li, Guiliang Liu

CoRR, 2024

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

CoRR, 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

Robust Inverse Constrained Reinforcement Learning under Model Misspecification.

Sheng Xu, Guiliang Liu

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

Confidence Aware Inverse Constrained Reinforcement Learning.

Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart

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

Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation.

Guorui Quan, Zhiqiang Xu, Guiliang Liu

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

Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning.

Sheng Xu, Guiliang Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Modelling Competitive Behaviors in Autonomous Driving Under Generative World Model.

Guanren Qiao, Guorui Quan, Rongxiao Qu, Guiliang Liu

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Unimodal Training-Multimodal Prediction: Cross-modal Federated Learning with Hierarchical Aggregation.

Rongyu Zhang, Xiaowei Chi, Guiliang Liu, Wenyi Zhang, Yuan Du, Fangxin Wang

CoRR, 2023

Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations.

Guanren Qiao, Guiliang Liu, Pascal Poupart, Zhiqiang Xu

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

An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient.

Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan

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

Benchmarking Constraint Inference in Inverse Reinforcement Learning.

Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning Soft Constraints From Constrained Expert Demonstrations.

Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart

Proceedings of the Eleventh International Conference on Learning Representations, 2023

NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge.

Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game.

Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Distributional Reinforcement Learning with Monotonic Splines.

Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart

Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning Object-Oriented Dynamics for Planning from Text.

Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart

Proceedings of the Tenth International Conference on Learning Representations, 2022

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 Tree Interpretation from Object Representation for Deep Reinforcement Learning.

Guiliang Liu, Xiangyu Sun, Oliver Schulte, Pascal Poupart

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Extracting Knowledge from Web Text with Monte Carlo Tree Search.

Guiliang Liu, Xu Li, Jiakang Wang, Mingming Sun, Ping Li

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

An Advantage Actor-Critic Algorithm with Confidence Exploration for Open Information Extraction.

Guiliang Liu, Xu Li, Mingming Sun, Ping Li

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Learning Agent Representations for Ice Hockey.

Guiliang Liu, Oliver Schulte, Pascal Poupart, Mike Rudd, Mehrsan Javan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cracking the Black Box: Distilling Deep Sports Analytics.

Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2018

Interpreting Deep Sports Analytics: Valuing Actions and Players in the NHL.

Guiliang Liu, Wang Zhu, Oliver Schulte

Proceedings of the 5th Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2018 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2018), 2018

Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees.

Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation.

Guiliang Liu, Oliver Schulte

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018