Tongzhou Mu

Orcid: 0000-0003-4384-2526

According to our database1, Tongzhou Mu authored at least 14 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulation.
IEEE Trans. Robotics, June, 2023

Unleashing the Creative Mind: Language Model As Hierarchical Policy For Improved Exploration on Challenging Problem Solving.
CoRR, 2023

Boosting Reinforcement Learning and Planning with Demonstrations: A Survey.
CoRR, 2023

Abstract-to-Executable Trajectory Translation for One-Shot Task Generalization.
Proceedings of the International Conference on Machine Learning, 2023

On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline.
Proceedings of the International Conference on Machine Learning, 2023

ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning.
Trans. Mach. Learn. Res., 2022

Close the Visual Domain Gap by Physics-Grounded Active Stereovision Depth Sensor Simulation.
CoRR, 2022

2021
ManiSkill: Learning-from-Demonstrations Benchmark for Generalizable Manipulation Skills.
CoRR, 2021

ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations.
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.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

State Alignment-based Imitation Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

2017
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016
Adaptive Variance Reducing for Stochastic Gradient Descent.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016


  Loading...