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Learning to Synthesize Programs as Interpretable and Generalizable Policies
NeurIPS 2021
Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, Joseph J. Lim
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Learning to Synthesize Programs as Interpretable and Generalizable Policies
Hierarchical Reinforcement Learning by Discovering Intrinsic Options
ICLR 2021
Jesse Zhang, Haonan Yu, Wei Xu
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Hierarchical Reinforcement Learning by Discovering Intrinsic Options
COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning
CoRL 2020
Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine
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COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings
ICML 2020
Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman
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Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings
TripAware: Emotional and Informational Approaches to Encourage Sustainable Transportation via Mobile Applications
ACM BuildSys 2019
Jesse Zhang, John Sullivan, Vasudev Venkatesh PB, Kyle Tse, Andy Yan, John Leyden, Kalyanaraman Shankari, Randy H Katz
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TripAware: Emotional and Informational Approaches to Encourage Sustainable Transportation via Mobile Applications
Replab: A reproducible low-cost arm benchmark platform for robotic learning
ICRA 2019
Brian Yang, Jesse Zhang, Vitchyr Pong, Sergey Levine, Dinesh Jayaraman
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Replab: A reproducible low-cost arm benchmark platform for robotic learning