Zheng Tian

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 32

Top Topics

Reinforcement Learning

Quadruped Robot

Diffusion Models

Top Venues

Publications

Yang Li, Fanglei Sun, Jingchen Hu, Chang Liu, Fan Wu, Kai Li, Ying Wen, Zheng Tian, Yaodong Yang, Jiangcheng Zhu, Zhifeng Chen, Jun Wang, Yang Yang
Self-Supervised MAFENN for Classifying Low-Labeled Distorted Images Over Mobile Fading Channels. IEEE Trans. Mob. Comput. 23 (8) (2024)
Kangning Yin, Shihao Zou, Yuxuan Ge, Zheng Tian
Tri-Modal Motion Retrieval by Learning a Joint Embedding Space. CoRR (2024)
Yan Song, He Jiang, Zheng Tian, Haifeng Zhang, Yingping Zhang, Jiangcheng Zhu, Zonghong Dai, Weinan Zhang, Jun Wang
An Empirical Study on Google Research Football Multi-agent Scenarios. Mach. Intell. Res. 21 (3) (2024)
Haoran Lang, Yuxuan Ge, Zheng Tian
S2DM: Sector-Shaped Diffusion Models for Video Generation. CoRR (2024)
Yuxuan Mu, Shihao Zou, Kangning Yin, Zheng Tian, Li Cheng, Weinan Zhang, Jun Wang
RACon: Retrieval-Augmented Simulated Character Locomotion Control. CoRR (2024)
Yan Song, He Jiang, Haifeng Zhang, Zheng Tian, Weinan Zhang, Jun Wang
Boosting Studies of Multi-Agent Reinforcement Learning on Google Research Football Environment: The Past, Present, and Future. AAMAS (2024)
Yang Li, Cheng Yu, Guangzhi Sun, Weiqin Zu, Zheng Tian, Ying Wen, Wei Pan, Chao Zhang, Jun Wang, Yang Yang, Fanglei Sun
Cross-Utterance Conditioned VAE for Speech Generation. CoRR (2023)
Mingcheng Chen, Haoran Zhao, Yuxiang Zhao, Hulei Fan, Hongqiao Gao, Yong Yu, Zheng Tian
ROMO: Retrieval-enhanced Offline Model-based Optimization. DAI (2023)
Hang Lai, Weinan Zhang, Xialin He, Chen Yu, Zheng Tian, Yong Yu, Jun Wang
Sim-to-Real Transfer for Quadrupedal Locomotion via Terrain Transformer. ICRA (2023)
Chen Yu, Weinan Zhang, Hang Lai, Zheng Tian, Laurent Kneip, Jun Wang
Multi-embodiment Legged Robot Control as a Sequence Modeling Problem. ICRA (2023)
Xihuai Wang, Zheng Tian, Ziyu Wan, Ying Wen, Jun Wang, Weinan Zhang
Order Matters: Agent-by-agent Policy Optimization. ICLR (2023)
Mingcheng Chen, Haoran Zhao, Yuxiang Zhao, Hulei Fan, Hongqiao Gao, Yong Yu, Zheng Tian
ROMO: Retrieval-enhanced Offline Model-based Optimization. CoRR (2023)
Xihuai Wang, Zheng Tian, Ziyu Wan, Ying Wen, Jun Wang, Weinan Zhang
Order Matters: Agent-by-agent Policy Optimization. CoRR (2023)
Ying Wen, Ziyu Wan, Ming Zhou, Shufang Hou, Zhe Cao, Chenyang Le, Jingxiao Chen, Zheng Tian, Weinan Zhang, Jun Wang
On Realization of Intelligent Decision-Making in the Real World: A Foundation Decision Model Perspective. CoRR (2022)
Chen Yu, Weinan Zhang, Hang Lai, Zheng Tian, Laurent Kneip, Jun Wang
Multi-embodiment Legged Robot Control as a Sequence Modeling Problem. CoRR (2022)
Hang Lai, Weinan Zhang, Xialin He, Chen Yu, Zheng Tian, Yong Yu, Jun Wang
Sim-to-Real Transfer for Quadrupedal Locomotion via Terrain Transformer. CoRR (2022)
Wenbin Song, Mingrui Zhang, Joseph G. Wallwork, Junpeng Gao, Zheng Tian, Fanglei Sun, Matthew D. Piggott, Junqing Chen, Zuoqiang Shi, Xiang Chen, Jun Wang
M2N: Mesh Movement Networks for PDE Solvers. CoRR (2022)
Ying Wen, Hui Chen, Yaodong Yang, Minne Li, Zheng Tian, Xu Chen, Jun Wang
A Game-Theoretic Approach to Multi-agent Trust Region Optimization. DAI (2022)
Le Cong Dinh, Stephen Marcus McAleer, Zheng Tian, Nicolas Perez Nieves, Oliver Slumbers, David Henry Mguni, Jun Wang, Haitham Bou-Ammar, Yaodong Yang
Online Double Oracle. Trans. Mach. Learn. Res. 2022 (2022)
Ying Wen, Hui Chen, Yaodong Yang, Zheng Tian, Minne Li, Xu Chen, Jun Wang
A Game-Theoretic Approach to Multi-Agent Trust Region Optimization. CoRR (2021)
Shangding Gu, Jakub Grudzien Kuba, Muning Wen, Ruiqing Chen, Ziyan Wang, Zheng Tian, Jun Wang, Alois C. Knoll, Yaodong Yang
Multi-Agent Constrained Policy Optimisation. CoRR (2021)
Le Cong Dinh, Yaodong Yang, Zheng Tian, Nicolas Perez Nieves, Oliver Slumbers, David Henry Mguni, Haitham Bou-Ammar, Jun Wang
Online Double Oracle. CoRR (2021)
Ming Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Aurora Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Dong Chen, Zhengbang Zhu, Nhat M. Nguyen, Mohamed Elsayed, Kun Shao, Sanjeevan Ahilan, Baokuan Zhang, Jiannan Wu, Zhengang Fu, Kasra Rezaee, Peyman Yadmellat, Mohsen Rohani, Nicolas Perez Nieves, Yihan Ni, Seyedershad Banijamali, Alexander Imani Cowen-Rivers, Zheng Tian, Daniel Palenicek, Haitham Bou-Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, Jun Wang
SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving. CoRR (2020)
Ian Davies, Zheng Tian, Jun Wang
Learning to Model Opponent Learning. CoRR (2020)
Zheng Tian, Shihao Zou, Ian Davies, Tim Warr, Lisheng Wu, Haitham Bou-Ammar, Jun Wang
Learning to Communicate Implicitly by Actions. AAAI (2020)
Ian Davies, Zheng Tian, Jun Wang
Learning to Model Opponent Learning (Student Abstract). AAAI (2020)
Ming Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Zhengbang Zhu, Yihan Ni, Nhat M. Nguyen, Mohamed Elsayed, Haitham Ammar, Alexander Imani Cowen-Rivers, Sanjeevan Ahilan, Zheng Tian, Daniel Palenicek, Kasra Rezaee, Peyman Yadmellat, Kun Shao, Dong Chen, Baokuan Zhang, Hongbo Zhang, Jianye Hao, Wulong Liu, Jun Wang
SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving. CoRL (2020)
Zheng Tian, Ying Wen, Zhichen Gong, Faiz Punakkath, Shihao Zou, Jun Wang
A Regularized Opponent Model with Maximum Entropy Objective. CoRR (2019)
Zheng Tian, Ying Wen, Zhichen Gong, Faiz Punakkath, Shihao Zou, Jun Wang
A Regularized Opponent Model with Maximum Entropy Objective. IJCAI (2019)
Zheng Tian, Shihao Zou, Tim Warr, Lisheng Wu, Jun Wang
Learning Multi-agent Implicit Communication Through Actions: A Case Study in Contract Bridge, a Collaborative Imperfect-Information Game. CoRR (2018)
Thomas Anthony, Zheng Tian, David Barber
Thinking Fast and Slow with Deep Learning and Tree Search. CoRR (2017)
Thomas Anthony, Zheng Tian, David Barber
Thinking Fast and Slow with Deep Learning and Tree Search. NIPS (2017)