Tongzhou Mu

According to our database, Tongzhou Mu authored at least 23 papers between 2016 and 2025.

Collaborative distances:

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

2025

Towards Embodiment Scaling Laws in Robot Locomotion.

Bo Ai, Liu Dai, Nico Bohlinger, Dichen Li, Tongzhou Mu, Zhanxin Wu, K. Fay, Henrik I. Christensen, Jan Peters, Hao Su

CoRR, May, 2025

Multi-Stage Manipulation with Demonstration-Augmented Reward, Policy, and World Model Learning.

Adrià López Escoriza, Nicklas Hansen, Stone Tao, Tongzhou Mu, Hao Su

CoRR, March, 2025

Responsive Noise-Relaying Diffusion Policy: Responsive and Efficient Visuomotor Control.

Zhuoqun Chen, Xiu Yuan, Tongzhou Mu, Hao Su

Trans. Mach. Learn. Res., 2025

Policy Decorator: Model-Agnostic Online Refinement for Large Policy Model.

Xiu Yuan, Tongzhou Mu, Stone Tao, Yunhao Fang, Mengke Zhang, Hao Su

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

When Should We Prefer State-to-Visual DAgger over Visual Reinforcement Learning?

Tongzhou Mu, Zhaoyang Li, Stanislaw Wiktor Strzelecki, Xiu Yuan, Yunchao Yao, Litian Liang, Hao Su

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Modeling the Physical World for Data-Centric Robotics

Tongzhou Mu

PhD thesis, 2024

ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI.

Stone Tao, Fanbo Xiang, Arth Shukla, Yuzhe Qin, Xander Hinrichsen, Xiaodi Yuan, Chen Bao, Xinsong Lin, Yulin Liu, Tse-kai Chan, Yuan Gao, Xuanlin Li, Tongzhou Mu, Nan Xiao, Arnav Gurha, Zhiao Huang, Roberto Calandra, Rui Chen, Shan Luo, Hao Su

CoRR, 2024

AdaDemo: Data-Efficient Demonstration Expansion for Generalist Robotic Agent.

Tongzhou Mu, Yijie Guo, Jie Xu, Ankit Goyal, Hao Su, Dieter Fox, Animesh Garg

CoRR, 2024

DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks.

Tongzhou Mu, Minghua Liu, Hao Su

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulation.

Xiaoshuai Zhang, Rui Chen, Ang Li, Fanbo Xiang, Yuzhe Qin, Jiayuan Gu, Zhan Ling, Minghua Liu, Peiyu Zeng, Songfang Han, Zhiao Huang, Tongzhou Mu, Jing Xu, Hao Su

IEEE Trans. Robotics, June, 2023

Unleashing the Creative Mind: Language Model As Hierarchical Policy For Improved Exploration on Challenging Problem Solving.

Zhan Ling, Yunhao Fang, Xuanlin Li, Tongzhou Mu, Mingu Lee, Reza Pourreza, Roland Memisevic, Hao Su

CoRR, 2023

Boosting Reinforcement Learning and Planning with Demonstrations: A Survey.

Tongzhou Mu, Hao Su

CoRR, 2023

Abstract-to-Executable Trajectory Translation for One-Shot Task Generalization.

Stone Tao, Xiaochen Li, Tongzhou Mu, Zhiao Huang, Yuzhe Qin, Hao Su

Proceedings of the International Conference on Machine Learning, 2023

On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline.

Nicklas Hansen, Zhecheng Yuan, Yanjie Ze, Tongzhou Mu, Aravind Rajeswaran, Hao Su, Huazhe Xu, Xiaolong Wang

Proceedings of the International Conference on Machine Learning, 2023

ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills.

Jiayuan Gu, Fanbo Xiang, Xuanlin Li, Zhan Ling, Xiqiang Liu, Tongzhou Mu, Yihe Tang, Stone Tao, Xinyue Wei, Yunchao Yao, Xiaodi Yuan, Pengwei Xie, Zhiao Huang, Rui Chen, Hao Su

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning.

Tongzhou Mu, Kaixiang Lin, Feiyang Niu, Govind Thattai

Trans. Mach. Learn. Res., 2022

Close the Visual Domain Gap by Physics-Grounded Active Stereovision Depth Sensor Simulation.

Xiaoshuai Zhang, Rui Chen, Fanbo Xiang, Yuzhe Qin, Jiayuan Gu, Zhan Ling, Minghua Liu, Peiyu Zeng, Songfang Han, Zhiao Huang, Tongzhou Mu, Jing Xu, Hao Su

CoRR, 2022

2021

ManiSkill: Learning-from-Demonstrations Benchmark for Generalizable Manipulation Skills.

Tongzhou Mu, Zhan Ling, Fanbo Xiang, Derek Yang, Xuanlin Li, Stone Tao, Zhiao Huang, Zhiwei Jia, Hao Su

CoRR, 2021

ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations.

Tongzhou Mu, Zhan Ling, Fanbo Xiang, Derek Yang, Xuanlin Li, Stone Tao, Zhiao Huang, Zhiwei Jia, Hao Su

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals.

Tongzhou Mu, Jiayuan Gu, Zhiwei Jia, Hao Tang, Hao Su

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

State Alignment-based Imitation Learning.

Fangchen Liu, Zhan Ling, Tongzhou Mu, Hao Su

Proceedings of the 8th International Conference on Learning Representations, 2020

2017

Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization.

Zebang Shen, Hui Qian, Tongzhou Mu, Chao Zhang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Adaptive Variance Reducing for Stochastic Gradient Descent.

Zebang Shen, Hui Qian, Tengfei Zhou, Tongzhou Mu

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016