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Kyle Hatch
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Conference and Workshop Papers
- 2024
- [c7]Victor Kolev, Rafael Rafailov, Kyle Hatch, Jiajun Wu, Chelsea Finn:
Efficient imitation learning with conservative world models. L4DC 2024: 1777-1790 - 2023
- [c6]Rafael Rafailov, Kyle Beltran Hatch, Victor Kolev, John D. Martin, Mariano Phielipp, Chelsea Finn:
MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning. CoRL 2023: 3654-3671 - [c5]Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta:
Train Offline, Test Online: A Real Robot Learning Benchmark. ICRA 2023: 9197-9203 - [c4]Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn:
Contrastive Example-Based Control. L4DC 2023: 155-169 - 2022
- [c3]John Mern, Sidhart Krishnan, Anil Yildiz, Kyle Hatch, Mykel J. Kochenderfer:
Interpretable Local Tree Surrogate Policies. SafeAI@AAAI 2022 - [c2]John Mern, Kyle Hatch, Ryan Silva, Cameron Hickert, Tamim Sookoor, Mykel J. Kochenderfer:
Autonomous Attack Mitigation for Industrial Control Systems. DSN Workshops 2022: 28-36 - 2021
- [c1]Ransalu Senanayake, Kyle Beltran Hatch, Jason Zheng, Mykel J. Kochenderfer:
3D Radar Velocity Maps for Uncertain Dynamic Environments. IROS 2021: 4854-4860
Informal and Other Publications
- 2024
- [i10]Rafael Rafailov, Kyle Hatch, Victor Kolev, John D. Martin, Mariano Phielipp, Chelsea Finn:
MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning. CoRR abs/2401.03306 (2024) - [i9]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) - [i8]Victor Kolev, Rafael Rafailov, Kyle Hatch, Jiajun Wu, Chelsea Finn:
Efficient Imitation Learning with Conservative World Models. CoRR abs/2405.13193 (2024) - 2023
- [i7]Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta:
Train Offline, Test Online: A Real Robot Learning Benchmark. CoRR abs/2306.00942 (2023) - [i6]Kyle Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn:
Contrastive Example-Based Control. CoRR abs/2307.13101 (2023) - 2021
- [i5]John Mern, Kyle Hatch, Ryan Silva, Jeff Brush, Mykel J. Kochenderfer:
Reinforcement Learning for Industrial Control Network Cyber Security Orchestration. CoRR abs/2106.05332 (2021) - [i4]Ransalu Senanayake, Kyle Beltran Hatch, Jason Zheng, Mykel J. Kochenderfer:
3D Radar Velocity Maps for Uncertain Dynamic Environments. CoRR abs/2107.11039 (2021) - [i3]John Mern, Sidhart Krishnan, Anil Yildiz, Kyle Hatch, Mykel J. Kochenderfer:
Interpretable Local Tree Surrogate Policies. CoRR abs/2109.08180 (2021) - [i2]John Mern, Kyle Hatch, Ryan Silva, Cameron Hickert, Tamim Sookoor, Mykel J. Kochenderfer:
Autonomous Attack Mitigation for Industrial Control Systems. CoRR abs/2111.02445 (2021) - 2020
- [i1]Kyle Hatch, John Mern, Mykel J. Kochenderfer:
Obstacle Avoidance Using a Monocular Camera. CoRR abs/2012.01608 (2020)
Coauthor Index
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