Yecheng Jason Ma

According to our database, Yecheng Jason Ma authored at least 22 papers between 2020 and 2024.

Collaborative distances:

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

2024

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.

Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna, Sudeep Dasari, Siddharth Karamcheti, Soroush Nasiriany, Mohan Kumar Srirama, Lawrence Yunliang Chen, Kirsty Ellis, Peter David Fagan, Joey Hejna, Masha Itkina, Marion Lepert, Yecheng Jason Ma, Patrick Tree Miller, Jimmy Wu, Suneel Belkhale, Shivin Dass, Huy Ha, Arhan Jain, Abraham Lee, Youngwoon Lee, Marius Memmel, Sungjae Park, Ilija Radosavovic, Kaiyuan Wang, Albert Zhan, Kevin Black, Cheng Chi, Kyle Beltran Hatch, Shan Lin, Jingpei Lu, Jean Mercat, Abdul Rehman, Pannag R. Sanketi, Archit Sharma, Cody Simpson, Quan Vuong, Homer Rich Walke, Blake Wulfe, Ted Xiao, Jonathan Heewon Yang, Arefeh Yavary, Tony Z. Zhao, Christopher Agia, Rohan Baijal, Mateo Guaman Castro, Daphne Chen, Qiuyu Chen, Trinity Chung, Jaimyn Drake, Ethan Paul Foster, et al.

CoRR, 2024

2023

Eureka: Human-Level Reward Design via Coding Large Language Models.

Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar

CoRR, 2023

Universal Visual Decomposer: Long-Horizon Manipulation Made Easy.

Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs

CoRR, 2023

LIV: Language-Image Representations and Rewards for Robotic Control.

Yecheng Jason Ma, William Liang, Vaidehi Som, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman

CoRR, 2023

TOM: Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching.

Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman

CoRR, 2023

Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?

Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Pieter Abbeel, Jitendra Malik, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier

CoRR, 2023

Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?

Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Tingfan Wu, Jay Vakil, Pieter Abbeel, Jitendra Malik, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching.

Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman

Proceedings of the Learning for Dynamics and Control Conference, 2023

LIV: Language-Image Representations and Rewards for Robotic Control.

Yecheng Jason Ma, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman

Proceedings of the International Conference on Machine Learning, 2023

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training.

Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Uniformly Conservative Exploration in Reinforcement Learning.

Wanqiao Xu, Yecheng Jason Ma, Kan Xu, Hamsa Bastani, Osbert Bastani

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression.

Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani

CoRR, 2022

SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching.

Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani

CoRR, 2022

Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression.

Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Regret Bounds for Risk-Sensitive Reinforcement Learning.

Osbert Bastani, Yecheng Jason Ma, Estelle Shen, Wanqiao Xu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching.

Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani

Proceedings of the International Conference on Machine Learning, 2022

Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning.

Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Safe Human-Interactive Control via Shielding.

Jeevana Priya Inala, Yecheng Jason Ma, Osbert Bastani, Xin Zhang, Armando Solar-Lezama

CoRR, 2021

Conservative Offline Distributional Reinforcement Learning.

Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

State Relevance for Off-Policy Evaluation.

Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez

Proceedings of the 38th International Conference on Machine Learning, 2021

Likelihood-Based Diverse Sampling for Trajectory Forecasting.

Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Diverse Sampling for Normalizing Flow Based Trajectory Forecasting.

Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani

CoRR, 2020