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We present our findings in the gap between theory and practice of using conditional energy-based models (EBM) as an implicit representation for behavior-cloned policies.
A tutorial on energy-based learning
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On variational bounds of mutual information
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On mutual information maximization for representation learning
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A simple framework for contrastive learning of visual representations
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How to train your energy-based model for regression
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Maximum entropy rl (provably) solves some robust rl problems
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Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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How to train your energy-based models
Yang Song and Diederik P Kingma · 2021
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Cooperative training of fast thinking initializer and slow thinking solver for conditional learning
Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, and Ying Nian Wu · 2021
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Implicit behavioral cloning
Pete Florence, Corey Lynch, Andy Zeng, Oscar A Ramirez, Ayzaan Wahid, Laura Downs, Adrian Wong, Johnny Lee, Igor Mordatch, and Jonathan Tompson · 2022
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Metropolis-adjusted langevin algorithm. Wikipedia, the free encyclopedia, 2022
Wikipedia contributors · 2022
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Benjamin Eysenbach and Sergey Levine · 2021
Cited alongside, same era.