Huazhe(Harry) Xu
Huazhe(Harry) Xu
UC Berkleley
Verified email at - Homepage
Cited by
Cited by
End-to-end learning of driving models from large-scale video datasets
H Xu, Y Gao, F Yu, T Darrell
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Natural language object retrieval
R Hu, H Xu, M Rohrbach, J Feng, K Saenko, T Darrell
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
Reinforcement learning from imperfect demonstrations
Y Gao, H Xu, J Lin, F Yu, S Levine, T Darrell
arXiv preprint arXiv:1802.05313, 2018
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees
Y Luo, H Xu, Y Li, Y Tian, T Darrell, T Ma
International Conference of Learning Representation (ICLR), https://arxiv …, 2019
Disentangling propagation and generation for video prediction
H Gao, H Xu, QZ Cai, R Wang, F Yu, T Darrell
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Modular architecture for starcraft ii with deep reinforcement learning
D Lee, H Tang, JO Zhang, H Xu, T Darrell, P Abbeel
Fourteenth Artificial Intelligence and Interactive Digital Entertainment …, 2018
Multi-task reinforcement learning with soft modularization
R Yang, H Xu, Y Wu, X Wang
arXiv preprint arXiv:2003.13661, 2020
Low-complexity LSQR-based linear precoding for massive MIMO systems
T Xie, Z Lu, Q Han, J Quan, B Wang
2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall), 1-5, 2015
Synthesizing Long-Term 3D Human Motion and Interaction in 3D Scenes
J Wang, H Xu, J Xu, S Liu, X Wang
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
BeBold: Exploration Beyond the Boundary of Explored Regions
T Zhang, H Xu, X Wang, Y Wu, K Keutzer, JE Gonzalez, Y Tian
arXiv preprint arXiv:2012.08621, 2020
Learning self-correctable policies and value functions from demonstrations with negative sampling
Y Luo, H Xu, T Ma
arXiv preprint arXiv:1907.05634, 2019
Video prediction via example guidance
J Xu, H Xu, B Ni, X Yang, T Darrell
International Conference on Machine Learning, 10628-10637, 2020
Hierarchical style-based networks for motion synthesis
J Xu, H Xu, B Ni, X Yang, X Wang, T Darrell
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization
Z Tang, C Yu, B Chen, H Xu, X Wang, F Fang, S Du, Y Wang, Y Wu
arXiv preprint arXiv:2103.04564, 2021
Solving Compositional Reinforcement Learning Problems via Task Reduction
Y Li, Y Wu, H Xu, X Wang, Y Wu
arXiv preprint arXiv:2103.07607, 2021
Multi-agent collaboration via reward attribution decomposition
T Zhang, H Xu, X Wang, Y Wu, K Keutzer, JE Gonzalez, Y Tian
arXiv preprint arXiv:2010.08531, 2020
Learning vision-guided quadrupedal locomotion end-to-end with cross-modal transformers
R Yang, M Zhang, N Hansen, H Xu, X Wang
arXiv preprint arXiv:2107.03996, 2021
Zero-shot Policy Learning with Spatial Temporal Reward Decomposition on Contingency-aware Observation
H Xu, B Chen, Y Gao, T Darrell
2021 IEEE International Conference on Robotics and Automation (ICRA), 10786 …, 2021
Hierarchical deep reinforcement learning agent with counter self-play on competitive games
H Xu, K Paster, Q Chen, H Tang, P Abbeel, T Darrell, S Levine
Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification
L Pan, L Huang, T Ma, H Xu
arXiv preprint arXiv:2111.11188, 2021
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