Chongyi Zheng

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I am an incoming PhD student in Computer Science at Princeton University advised by Benjamin Eysenbach. I have worked on developing reinforcement learning (RL) algorithms that enable long-horizon reasoning using probabilistic inference. I recently graduated from Carnegie Mellon University with a M.S. in Electrical and Computer Engineering advised by Ruslan Salakhutdinov. I have had the great opportunity to collaborate with Sergey Levine and work with Xiaolong Wang.

preprints

2023

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    Generalized Animal Imitator: Agile Locomotion with Versatile Motion Prior
    Ruihan Yang*, Zhuoqun Chen*, Jianhan Ma*, Chongyi Zheng*, Yiyu Chen, Quan Nguyen, and Xiaolong Wang
    arXiv preprint arXiv:2310.01408, 2023

publications

2024

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    Contrastive Difference Predictive Coding
    Chongyi Zheng, Ruslan Salakhutdinov, and Benjamin Eysenbach
    International Conference on Learning Representations, 2024
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    Stabilizing Contrastive RL: Techniques for Offline Goal Reaching
    Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, and Sergey Levine
    International Conference on Learning Representations (Spotlight Presentation < 5%), 2024

2023

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    BridgeData V2: A Dataset for Robot Learning at Scale
    Homer Walke, Kevin Black, Abraham Lee, Moo Jin Kim, Max Du, Chongyi Zheng, Tony Zhao, Philippe Hansen-Estruch, Quan Vuong, Andre He, Vivek Myers, Kuan Fang, Chelsea Finn, and Sergey Levine
    In Conference on Robot Learning, 2023

2021

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    Learning Domain Invariant Representations in Goal-conditioned Block MDPs
    Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael Zhang, and Jimmy Ba
    Advances in Neural Information Processing Systems, 2021

2020

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    Learning Nearly Decomposable Value Functions Via Communication Minimization
    Tonghan Wang*, Jianhao Wang*, Chongyi Zheng, and Chongjie Zhang
    In International Conference on Learning Representations, 2020