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2020 – today
- 2025
[i17]Huayi Zhou, Ruixiang Wang, Yunxin Tai, Yueci Deng, Guiliang Liu, Kui Jia:
You Only Teach Once: Learn One-Shot Bimanual Robotic Manipulation from Video Demonstrations. CoRR abs/2501.14208 (2025)- [i16]Sixu Lin, Guanren Qiao, Yunxin Tai, Ang Li, Kui Jia, Guiliang Liu:
HWC-Loco: A Hierarchical Whole-Body Control Approach to Robust Humanoid Locomotion. CoRR abs/2503.00923 (2025) - [i15]Ruixiang Wang, Huayi Zhou, Xinyue Yao, Guiliang Liu, Kui Jia:
GAT-Grasp: Gesture-Driven Affordance Transfer for Task-Aware Robotic Grasping. CoRR abs/2503.06227 (2025) - [i14]Quanyuan Ruan, Jiabao Lei, Wenhao Yuan, Yanglin Zhang, Dekun Lu, Guiliang Liu, Kui Jia:
Prof. Robot: Differentiable Robot Rendering Without Static and Self-Collisions. CoRR abs/2503.11269 (2025) - 2024
- [c21]Guanren Qiao, Guorui Quan, Rongxiao Qu, Guiliang Liu:
Modelling Competitive Behaviors in Autonomous Driving Under Generative World Model. ECCV (35) 2024: 19-36 - [c20]Sheng Xu, Guiliang Liu:
Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning. ICLR 2024 - [c19]Guorui Quan, Zhiqiang Xu, Guiliang Liu:
Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation. ICML 2024 - [c18]Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart:
Confidence Aware Inverse Constrained Reinforcement Learning. ICML 2024 - [c17]Sheng Xu, Guiliang Liu:
Robust Inverse Constrained Reinforcement Learning under Model Misspecification. ICML 2024 - [i13]Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart:
Confidence Aware Inverse Constrained Reinforcement Learning. CoRR abs/2406.16782 (2024) - [i12]Guanren Qiao, Guorui Quan, Jiawei Yu, Shujun Jia, Guiliang Liu:
TrafficGamer: Reliable and Flexible Traffic Simulation for Safety-Critical Scenarios with Game-Theoretic Oracles. CoRR abs/2408.15538 (2024) - [i11]Guiliang Liu, Sheng Xu, Shicheng Liu, Ashish Gaurav, Sriram Ganapathi Subramanian, Pascal Poupart:
A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges. CoRR abs/2409.07569 (2024) - [i10]Bo Yue, Jian Li, Guiliang Liu:
Provably Efficient Exploration in Inverse Constrained Reinforcement Learning. CoRR abs/2409.15963 (2024) - [i9]Nan Fang, Guiliang Liu, Wei Gong:
Offline Inverse Constrained Reinforcement Learning for Safe-Critical Decision Making in Healthcare. CoRR abs/2410.07525 (2024) - 2023
- [c16]Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart:
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge. AISTATS 2023: 1942-1964 - [c15]Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart:
Learning Soft Constraints From Constrained Expert Demonstrations. ICLR 2023 - [c14]Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart:
Benchmarking Constraint Inference in Inverse Reinforcement Learning. ICLR 2023 - [c13]Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan:
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. NeurIPS 2023 - [c12]Guanren Qiao, Guiliang Liu, Pascal Poupart, Zhiqiang Xu:
Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations. NeurIPS 2023 - [i8]Rongyu Zhang, Xiaowei Chi, Guiliang Liu, Wenyi Zhang
, Yuan Du, Fangxin Wang:
Unimodal Training-Multimodal Prediction: Cross-modal Federated Learning with Hierarchical Aggregation. CoRR abs/2303.15486 (2023) - [i7]Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan:
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. CoRR abs/2307.08873 (2023) - 2022
- [c11]Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart:
Learning Object-Oriented Dynamics for Planning from Text. ICLR 2022 - [c10]Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart:
Distributional Reinforcement Learning with Monotonic Splines. ICLR 2022 - [c9]Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart:
Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game. NeurIPS 2022 - [i6]Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart:
Learning Soft Constraints From Constrained Expert Demonstrations. CoRR abs/2206.01311 (2022) - [i5]Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart:
Benchmarking Constraint Inference in Inverse Reinforcement Learning. CoRR abs/2206.09670 (2022) - 2021
- [c8]Guiliang Liu, Xiangyu Sun, Oliver Schulte, Pascal Poupart:
Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning. NeurIPS 2021: 19622-19636 - [i4]Xiangyu Sun, Guiliang Liu, Pascal Poupart, Oliver Schulte:
NTS-NOTEARS: Learning Nonparametric Temporal DAGs With Time-Series Data and Prior Knowledge. CoRR abs/2109.04286 (2021) - 2020
- [j1]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): 1531-1559 (2020) - [c7]Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu:
Cracking the Black Box: Distilling Deep Sports Analytics. KDD 2020: 3154-3162 - [c6]Guiliang Liu, Oliver Schulte, Pascal Poupart, Mike Rudd, Mehrsan Javan:
Learning Agent Representations for Ice Hockey. NeurIPS 2020 - [c5]Guiliang Liu, Xu Li, Mingming Sun, Ping Li:
An Advantage Actor-Critic Algorithm with Confidence Exploration for Open Information Extraction. SDM 2020: 217-225 - [c4]Guiliang Liu, Xu Li, Jiakang Wang, Mingming Sun, Ping Li:
Extracting Knowledge from Web Text with Monte Carlo Tree Search. WWW 2020: 2585-2591 - [i3]Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu:
Cracking the Black Box: Distilling Deep Sports Analytics. CoRR abs/2006.04551 (2020)
2010 – 2019
- 2018
- [c3]Guiliang Liu, Oliver Schulte:
Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation. IJCAI 2018: 3442-3448 - [c2]Guiliang Liu, Wang Zhu, Oliver Schulte:
Interpreting Deep Sports Analytics: Valuing Actions and Players in the NHL. MLSA@PKDD/ECML 2018: 69-81 - [c1]Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li:
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees. ECML/PKDD (2) 2018: 414-429 - [i2]Guiliang Liu, Oliver Schulte:
Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation. CoRR abs/1805.11088 (2018) - [i1]Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li:
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees. CoRR abs/1807.05887 (2018)
Coauthor Index
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last updated on 2025-04-20 23:52 CEST by the dblp team
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