Yecheng Jason Ma

According to our database, Yecheng Jason Ma authored at least 25 papers between 2020 and 2024.

Collaborative distances:

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

2024

DrEureka: Language Model Guided Sim-To-Real Transfer.

Yecheng Jason Ma, William Liang, Hung-Ju Wang, Sam Wang, Yuke Zhu, Linxi Fan, Osbert Bastani, Dinesh Jayaraman

CoRR, 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

Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models.

Junyao Shi, Jianing Qian, Yecheng Jason Ma, Dinesh Jayaraman

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration.

Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Universal Visual Decomposer: Long-Horizon Manipulation Made Easy.

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

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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