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COMBO: Conservative Offline Model-Based Policy Optimization

Feb 16, 2021
Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn


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How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned

Feb 04, 2021
Julian Ibarz, Jie Tan, Chelsea Finn, Mrinal Kalakrishnan, Peter Pastor, Sergey Levine

* Journal of Robotics Research (IJRR), February 2021 

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Model-Based Visual Planning with Self-Supervised Functional Distances

Dec 30, 2020
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine


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Offline Reinforcement Learning from Images with Latent Space Models

Dec 21, 2020
Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn


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Variable-Shot Adaptation for Online Meta-Learning

Dec 14, 2020
Tianhe Yu, Xinyang Geng, Chelsea Finn, Sergey Levine

* First two authors contribute equally 

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WILDS: A Benchmark of in-the-Wild Distribution Shifts

Dec 14, 2020
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang


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Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning

Dec 08, 2020
Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, Dumitru Erhan


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Learning Latent Representations to Influence Multi-Agent Interaction

Nov 12, 2020
Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh

* Conference on Robot Learning (CoRL) 2020. Supplementary website at https://sites.google.com/view/latent-strategies/ 

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Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Nov 12, 2020
Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn


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Continual Learning of Control Primitives: Skill Discovery via Reset-Games

Nov 10, 2020
Kelvin Xu, Siddharth Verma, Chelsea Finn, Sergey Levine

* To appear at NeurIPS 2020 

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Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones

Oct 29, 2020
Brijen Thananjeyan, Ashwin Balakrishna, Suraj Nair, Michael Luo, Krishnan Srinivasan, Minho Hwang, Joseph E. Gonzalez, Julian Ibarz, Chelsea Finn, Ken Goldberg

* First two authors contributed equally 

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Measuring and Harnessing Transference in Multi-Task Learning

Oct 29, 2020
Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn


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Learning to be Safe: Deep RL with a Safety Critic

Oct 27, 2020
Krishnan Srinivasan, Benjamin Eysenbach, Sehoon Ha, Jie Tan, Chelsea Finn

* In submission, 16 pages (including appendix) 

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One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL

Oct 27, 2020
Saurabh Kumar, Aviral Kumar, Sergey Levine, Chelsea Finn

* Accepted at NeurIPS 2020 

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MELD: Meta-Reinforcement Learning from Images via Latent State Models

Oct 26, 2020
Tony Z. Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine

* Accepted to CoRL 2020. Supplementary material at https://sites.google.com/view/meld-lsm/home . 16 pages, 19 figures 

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Batch Exploration with Examples for Scalable Robotic Reinforcement Learning

Oct 22, 2020
Annie S. Chen, HyunJi Nam, Suraj Nair, Chelsea Finn

* 10 Pages, 9 Figures 

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Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings

Aug 15, 2020
Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman

* 15 pages, 8 figures, ICML 2020. Website with code: https://sites.google.com/berkeley.edu/carl 

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Offline Meta-Reinforcement Learning with Advantage Weighting

Aug 13, 2020
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn

* 8 pages main text; 18 pages total 

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Goal-Aware Prediction: Learning to Model What Matters

Aug 10, 2020
Suraj Nair, Silvio Savarese, Chelsea Finn


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Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning

Aug 06, 2020
Evan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn

* Project web page at https://ezliu.github.io/dream 

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Meta-Learning Symmetries by Reparameterization

Jul 06, 2020
Allan Zhou, Tom Knowles, Chelsea Finn


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Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift

Jul 06, 2020
Marvin Zhang, Henrik Marklund, Abhishek Gupta, Sergey Levine, Chelsea Finn

* Project website: https://sites.google.com/view/adaptive-risk-minimization ; Code: https://github.com/henrikmarklund/arm 

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Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors

Jun 23, 2020
Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

* Project page: orybkin.github.io/video-gcp 

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Deep Reinforcement Learning amidst Lifelong Non-Stationarity

Jun 18, 2020
Annie Xie, James Harrison, Chelsea Finn

* supplementary website at https://sites.google.com/stanford.edu/lilac/ 

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Meta-Reinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling

Jun 15, 2020
Russell Mendonca, Xinyang Geng, Chelsea Finn, Sergey Levine


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MOPO: Model-based Offline Policy Optimization

May 27, 2020
Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma

* First two authors contributed equally. Last two authors advised equally 

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Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation

Apr 21, 2020
Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman

* 8.5 pages, 9 figures. See video overview and experiments at https://youtu.be/pPDVewcSpdc and project website at https://ryanjulian.me/continual-fine-tuning 

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Weakly-Supervised Reinforcement Learning for Controllable Behavior

Apr 06, 2020
Lisa Lee, Benjamin Eysenbach, Ruslan Salakhutdinov, Shixiang, Gu, Chelsea Finn


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