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Yecheng Jason Ma
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2020 – today
- 2024
- [i17]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.:
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. CoRR abs/2403.12945 (2024) - [i16]Junyao Shi, Jianing Qian, Yecheng Jason Ma, Dinesh Jayaraman:
Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models. CoRR abs/2404.13474 (2024) - [i15]Yecheng Jason Ma, William Liang, Hung-Ju Wang, Sam Wang, Yuke Zhu, Linxi Fan, Osbert Bastani, Dinesh Jayaraman:
DrEureka: Language Model Guided Sim-To-Real Transfer. CoRR abs/2406.01967 (2024) - 2023
- [c12]Wanqiao Xu, Yecheng Jason Ma, Kan Xu, Hamsa Bastani, Osbert Bastani:
Uniformly Conservative Exploration in Reinforcement Learning. AISTATS 2023: 10856-10870 - [c11]Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang:
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. ICLR 2023 - [c10]Yecheng Jason Ma, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman:
LIV: Language-Image Representations and Rewards for Robotic Control. ICML 2023: 23301-23320 - [c9]Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman:
Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching. L4DC 2023: 259-271 - [c8]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:
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? NeurIPS 2023 - [i14]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:
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? CoRR abs/2303.18240 (2023) - [i13]Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman:
TOM: Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching. CoRR abs/2305.12663 (2023) - [i12]Yecheng Jason Ma, William Liang, Vaidehi Som, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman:
LIV: Language-Image Representations and Rewards for Robotic Control. CoRR abs/2306.00958 (2023) - [i11]Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs:
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy. CoRR abs/2310.08581 (2023) - [i10]Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar:
Eureka: Human-Level Reward Design via Coding Large Language Models. CoRR abs/2310.12931 (2023) - 2022
- [c7]Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman:
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning. AAAI 2022: 5404-5412 - [c6]Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani:
Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching. ICML 2022: 14639-14663 - [c5]Osbert Bastani, Yecheng Jason Ma, Estelle Shen, Wanqiao Xu:
Regret Bounds for Risk-Sensitive Reinforcement Learning. NeurIPS 2022 - [c4]Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani:
Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression. NeurIPS 2022 - [i9]Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani:
SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching. CoRR abs/2202.02433 (2022) - [i8]Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani:
How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression. CoRR abs/2206.03023 (2022) - [i7]Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang:
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. CoRR abs/2210.00030 (2022) - [i6]Osbert Bastani, Yecheng Jason Ma, Estelle Shen, Wanqiao Xu:
Regret Bounds for Risk-Sensitive Reinforcement Learning. CoRR abs/2210.05650 (2022) - 2021
- [c3]Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani:
Likelihood-Based Diverse Sampling for Trajectory Forecasting. ICCV 2021: 13259-13268 - [c2]Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez:
State Relevance for Off-Policy Evaluation. ICML 2021: 9537-9546 - [c1]Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani:
Conservative Offline Distributional Reinforcement Learning. NeurIPS 2021: 19235-19247 - [i5]Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani:
Conservative Offline Distributional Reinforcement Learning. CoRR abs/2107.06106 (2021) - [i4]Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez:
State Relevance for Off-Policy Evaluation. CoRR abs/2109.06310 (2021) - [i3]Jeevana Priya Inala, Yecheng Jason Ma, Osbert Bastani, Xin Zhang, Armando Solar-Lezama:
Safe Human-Interactive Control via Shielding. CoRR abs/2110.05440 (2021) - [i2]Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman:
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning. CoRR abs/2112.07701 (2021) - 2020
- [i1]Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani:
Diverse Sampling for Normalizing Flow Based Trajectory Forecasting. CoRR abs/2011.15084 (2020)
Coauthor Index
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last updated on 2024-07-29 21:27 CEST by the dblp team
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