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ORCIDChelsea Finn
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- affiliation: Stanford University, CA, USA
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2020 – today
- 2023
[i164]Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa M. Zintgraf, Chelsea Finn, Shimon Whiteson:
A Survey of Meta-Reinforcement Learning. CoRR abs/2301.08028 (2023)- [i163]Allan Zhou, Moo Jin Kim, Lirui Wang, Pete Florence, Chelsea Finn:
NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis. CoRR abs/2301.08556 (2023) - [i162]Eric Mitchell, Yoonho Lee, Alexander Khazatsky, Christopher D. Manning, Chelsea Finn:
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature. CoRR abs/2301.11305 (2023) - [i161]Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn:
Leveraging Domain Relations for Domain Generalization. CoRR abs/2302.02609 (2023) - [i160]Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine:
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. CoRR abs/2302.02931 (2023) - [i159]Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn:
Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features. CoRR abs/2302.05441 (2023) - [i158]Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang:
Language-Driven Representation Learning for Robotics. CoRR abs/2302.12766 (2023) - [i157]Allan Zhou, Kaien Yang, Kaylee Burns, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn:
Permutation Equivariant Neural Functionals. CoRR abs/2302.14040 (2023) - [i156]Austin Stone, Ted Xiao, Yao Lu, Keerthana Gopalakrishnan, Kuang-Huei Lee, Quan Vuong, Paul Wohlhart, Brianna Zitkovich, Fei Xia, Chelsea Finn, Karol Hausman:
Open-World Object Manipulation using Pre-trained Vision-Language Models. CoRR abs/2303.00905 (2023) - [i155]Archit Sharma, Ahmed M. Ahmed, Rehaan Ahmad, Chelsea Finn:
Self-Improving Robots: End-to-End Autonomous Visuomotor Reinforcement Learning. CoRR abs/2303.01488 (2023) - [i154]Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine:
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning. CoRR abs/2303.05479 (2023) - 2022
- [c120]Annie Xie, Chelsea Finn:
Lifelong Robotic Reinforcement Learning by Retaining Experiences. CoLLAs 2022: 838-855 - [c119]Brian Ichter, Anthony Brohan, Yevgen Chebotar, Chelsea Finn, Karol Hausman, Alexander Herzog, Daniel Ho, Julian Ibarz, Alex Irpan, Eric Jang, Ryan Julian, Dmitry Kalashnikov, Sergey Levine, Yao Lu, Carolina Parada, Kanishka Rao, Pierre Sermanet, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Mengyuan Yan, Noah Brown, Michael Ahn, Omar Cortes, Nicolas Sievers, Clayton Tan, Sichun Xu, Diego Reyes, Jarek Rettinghouse, Jornell Quiambao, Peter Pastor, Linda Luu, Kuang-Huei Lee, Yuheng Kuang, Sally Jesmonth, Nikhil J. Joshi, Kyle Jeffrey, Rosario Jauregui Ruano, Jasmine Hsu, Keerthana Gopalakrishnan, Byron David, Andy Zeng, Chuyuan Kelly Fu:
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. CoRL 2022: 287-318 - [c118]Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, Abhinav Gupta:
R3M: A Universal Visual Representation for Robot Manipulation. CoRL 2022: 892-909 - [c117]Kaylee Burns, Tianhe Yu, Chelsea Finn, Karol Hausman:
Offline Reinforcement Learning at Multiple Frequencies. CoRL 2022: 2041-2051 - [c116]Eric Mitchell, Joseph J. Noh, Siyan Li, William S. Armstrong, Ananth Agarwal, Patrick Liu, Chelsea Finn, Christopher D. Manning:
Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference. EMNLP 2022: 1754-1768 - [c115]Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, Sergey Levine:
CoMPS: Continual Meta Policy Search. ICLR 2022 - [c114]Kyle Hsu, Moo Jin Kim, Rafael Rafailov, Jiajun Wu, Chelsea Finn:
Vision-Based Manipulators Need to Also See from Their Hands. ICLR 2022 - [c113]Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, Christopher D. Manning:
Fast Model Editing at Scale. ICLR 2022 - [c112]Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo
, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang:
Extending the WILDS Benchmark for Unsupervised Adaptation. ICLR 2022 - [c111]Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn:
Autonomous Reinforcement Learning: Formalism and Benchmarking. ICLR 2022 - [c110]Huaxiu Yao, Linjun Zhang, Chelsea Finn:
Meta-Learning with Fewer Tasks through Task Interpolation. ICLR 2022 - [c109]Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn:
Do deep networks transfer invariances across classes? ICLR 2022 - [c108]Eric Mitchell, Charles Lin, Antoine Bosselut, Christopher D. Manning, Chelsea Finn:
Memory-Based Model Editing at Scale. ICML 2022: 15817-15831 - [c107]Archit Sharma, Rehaan Ahmad, Chelsea Finn:
A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning. ICML 2022: 19645-19657 - [c106]Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang:
Robust Policy Learning over Multiple Uncertainty Sets. ICML 2022: 24414-24429 - [c105]Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn:
Improving Out-of-Distribution Robustness via Selective Augmentation. ICML 2022: 25407-25437 - [c104]Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Chelsea Finn, Sergey Levine:
How to Leverage Unlabeled Data in Offline Reinforcement Learning. ICML 2022: 25611-25635 - [c103]Michael Zhang, Nimit Sharad Sohoni, Hongyang R. Zhang, Chelsea Finn, Christopher Ré:
Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations. ICML 2022: 26484-26516 - [i153]Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn:
Improving Out-of-Distribution Robustness via Selective Augmentation. CoRR abs/2201.00299 (2022) - [i152]Jathushan Rajasegaran, Chelsea Finn, Sergey Levine:
Fully Online Meta-Learning Without Task Boundaries. CoRR abs/2202.00263 (2022) - [i151]Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Chelsea Finn, Sergey Levine:
How to Leverage Unlabeled Data in Offline Reinforcement Learning. CoRR abs/2202.01741 (2022) - [i150]Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, Chelsea Finn:
BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning. CoRR abs/2202.02005 (2022) - [i149]Yoonho Lee, Huaxiu Yao, Chelsea Finn:
Diversify and Disambiguate: Learning From Underspecified Data. CoRR abs/2202.03418 (2022) - [i148]Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang:
Robust Policy Learning over Multiple Uncertainty Sets. CoRR abs/2202.07013 (2022) - [i147]Michael Zhang, Nimit Sharad Sohoni, Hongyang R. Zhang, Chelsea Finn, Christopher Ré:
Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations. CoRR abs/2203.01517 (2022) - [i146]Allan Zhou, Vikash Kumar, Chelsea Finn, Aravind Rajeswaran:
Policy Architectures for Compositional Generalization in Control. CoRR abs/2203.05960 (2022) - [i145]Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Yuan Gao, Jianhao Wang, Wenzhe Li, Bin Liang, Chelsea Finn, Chongjie Zhang:
Latent-Variable Advantage-Weighted Policy Optimization for Offline RL. CoRR abs/2203.08949 (2022) - [i144]Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn:
Do Deep Networks Transfer Invariances Across Classes? CoRR abs/2203.09739 (2022) - [i143]Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, Abhinav Gupta:
R3M: A Universal Visual Representation for Robot Manipulation. CoRR abs/2203.12601 (2022) - [i142]Kyle Hsu, Moo Jin Kim, Rafael Rafailov, Jiajun Wu, Chelsea Finn:
Vision-Based Manipulators Need to Also See from Their Hands. CoRR abs/2203.12677 (2022) - [i141]Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Daniel Ho, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan:
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. CoRR abs/2204.01691 (2022) - [i140]Ali Ghadirzadeh, Petra Poklukar, Karol Arndt, Chelsea Finn, Ville Kyrki, Danica Kragic, Mårten Björkman:
Training and Evaluation of Deep Policies using Reinforcement Learning and Generative Models. CoRR abs/2204.08573 (2022) - [i139]Archit Sharma, Rehaan Ahmad, Chelsea Finn:
A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning. CoRR abs/2205.05212 (2022) - [i138]Maximilian Du, Olivia Y. Lee, Suraj Nair, Chelsea Finn:
Play it by Ear: Learning Skills amidst Occlusion through Audio-Visual Imitation Learning. CoRR abs/2205.14850 (2022) - [i137]Eric Mitchell, Charles Lin, Antoine Bosselut, Christopher D. Manning, Chelsea Finn:
Memory-Based Model Editing at Scale. CoRR abs/2206.06520 (2022) - [i136]Kaylee Burns, Tianhe Yu, Chelsea Finn, Karol Hausman:
Offline Reinforcement Learning at Multiple Frequencies. CoRR abs/2207.13082 (2022) - [i135]Andrew Joohun Nam, Mengye Ren, Chelsea Finn, James L. McClelland:
Learning to Reason With Relational Abstractions. CoRR abs/2210.02615 (2022) - [i134]Aviral Kumar, Anikait Singh, Frederik Ebert, Yanlai Yang, Chelsea Finn, Sergey Levine:
Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials. CoRR abs/2210.05178 (2022) - [i133]Zhenbang Wu, Huaxiu Yao, Zhe Su, David M. Liebovitz, Lucas M. Glass, James Zou, Chelsea Finn, Jimeng Sun:
Knowledge-Driven New Drug Recommendation. CoRR abs/2210.05572 (2022) - [i132]Huaxiu Yao, Yiping Wang, Linjun Zhang, James Zou, Chelsea Finn:
C-Mixup: Improving Generalization in Regression. CoRR abs/2210.05775 (2022) - [i131]Annie S. Chen, Archit Sharma, Sergey Levine, Chelsea Finn:
You Only Live Once: Single-Life Reinforcement Learning. CoRR abs/2210.08863 (2022) - [i130]Annie Xie, Fahim Tajwar, Archit Sharma, Chelsea Finn:
When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning. CoRR abs/2210.10765 (2022) - [i129]Yoonho Lee, Annie S. Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, Chelsea Finn:
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts. CoRR abs/2210.11466 (2022) - [i128]Huaxiu Yao, Xinyu Yang, Allan Zhou, Chelsea Finn:
Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations. CoRR abs/2210.14358 (2022) - [i127]Evan Zheran Liu, Moritz Stephan, Allen Nie, Chris Piech, Emma Brunskill, Chelsea Finn:
Giving Feedback on Interactive Student Programs with Meta-Exploration. CoRR abs/2211.08802 (2022) - [i126]Eric Mitchell, Joseph J. Noh, Siyan Li, William S. Armstrong, Ananth Agarwal, Patrick Liu, Chelsea Finn, Christopher D. Manning:
Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference. CoRR abs/2211.11875 (2022) - [i125]Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei Koh, Chelsea Finn:
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time. CoRR abs/2211.14238 (2022) - [i124]Eric Mitchell, Peter Henderson, Christopher D. Manning, Dan Jurafsky, Chelsea Finn:
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models. CoRR abs/2211.14946 (2022) - [i123]Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, Zico Kolter, Chelsea Finn:
Learning Options via Compression. CoRR abs/2212.04590 (2022) - [i122]Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Tomas Jackson, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Kuang-Huei Lee, Sergey Levine, Yao Lu, Utsav Malla, Deeksha Manjunath, Igor Mordatch, Ofir Nachum, Carolina Parada, Jodilyn Peralta, Emily Perez, Karl Pertsch, Jornell Quiambao, Kanishka Rao, Michael S. Ryoo, Grecia Salazar, Pannag Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich:
RT-1: Robotics Transformer for Real-World Control at Scale. CoRR abs/2212.06817 (2022) - 2021
- [j5]Julian Ibarz, Jie Tan, Chelsea Finn, Mrinal Kalakrishnan, Peter Pastor, Sergey Levine:
How to train your robot with deep reinforcement learning: lessons we have learned. Int. J. Robotics Res. 40(4-5) (2021) - [j4]Annie S. Chen, HyunJi Nam, Suraj Nair, Chelsea Finn:
Batch Exploration With Examples for Scalable Robotic Reinforcement Learning. IEEE Robotics Autom. Lett. 6(3): 4401-4408 (2021) - [j3]Brijen Thananjeyan, Ashwin Balakrishna, Suraj Nair, Michael Luo, Krishnan Srinivasan, Minho Hwang, Joseph E. Gonzalez, Julian Ibarz, Chelsea Finn, Ken Goldberg:
Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones. IEEE Robotics Autom. Lett. 6(3): 4915-4922 (2021) - [c102]Eric Mitchell, Chelsea Finn, Christopher D. Manning:
Challenges of Acquiring Compositional Inductive Biases via Meta-Learning. MetaDL@AAAI 2021: 138-148 - [c101]Bohan Wu, Suraj Nair, Li Fei-Fei, Chelsea Finn:
Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks. CoRL 2021: 1-13 - [c100]Aviral Kumar, Anikait Singh, Stephen Tian, Chelsea Finn, Sergey Levine:
A Workflow for Offline Model-Free Robotic Reinforcement Learning. CoRL 2021: 417-428 - [c99]Dmitry Kalashnikov, Jake Varley, Yevgen Chebotar, Benjamin Swanson, Rico Jonschkowski, Chelsea Finn, Sergey Levine, Karol Hausman:
Scaling Up Multi-Task Robotic Reinforcement Learning. CoRL 2021: 557-575 - [c98]Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, Chelsea Finn:
BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning. CoRL 2021: 991-1002 - [c97]Suraj Nair, Eric Mitchell, Kevin Chen, Brian Ichter, Silvio Savarese, Chelsea Finn:
Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation. CoRL 2021: 1303-1315 - [c96]Bohan Wu, Suraj Nair, Roberto Martín-Martín, Li Fei-Fei, Chelsea Finn:
Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction. CVPR 2021: 2318-2328 - [c95]Glen Berseth, Daniel Geng, Coline Manon Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine:
SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments. ICLR 2021 - [c94]Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine:
Model-Based Visual Planning with Self-Supervised Functional Distances. ICLR 2021 - [c93]Allan Zhou, Tom Knowles, Chelsea Finn:
Meta-learning Symmetries by Reparameterization. ICLR 2021 - [c92]Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine:
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. ICML 2021: 1518-1528 - [c91]Jared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Ré, Chelsea Finn, Percy Liang:
Catformer: Designing Stable Transformers via Sensitivity Analysis. ICML 2021: 2489-2499 - [c90]Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran S. Haque, Sara M. Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang:
WILDS: A Benchmark of in-the-Wild Distribution Shifts. ICML 2021: 5637-5664 - [c89]Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn:
Just Train Twice: Improving Group Robustness without Training Group Information. ICML 2021: 6781-6792 - [c88]Evan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn:
Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices. ICML 2021: 6925-6935 - [c87]Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn:
Offline Meta-Reinforcement Learning with Advantage Weighting. ICML 2021: 7780-7791 - [c86]Annie Xie, James Harrison, Chelsea Finn:
Deep Reinforcement Learning amidst Continual Structured Non-Stationarity. ICML 2021: 11393-11403 - [c85]Ali Ghadirzadeh, Xi Chen, Petra Poklukar, Chelsea Finn, Mårten Björkman, Danica Kragic:
Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms. IROS 2021: 1274-1280 - [c84]Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn:
Offline Reinforcement Learning from Images with Latent Space Models. L4DC 2021: 1154-1168 - [c83]Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn:
Visual Adversarial Imitation Learning using Variational Models. NeurIPS 2021: 3016-3028 - [c82]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. NeurIPS 2021: 7497-7509 - [c81]Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D. Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine:
Information is Power: Intrinsic Control via Information Capture. NeurIPS 2021: 10745-10758 - [c80]Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn:
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning. NeurIPS 2021: 11501-11516 - [c79]Ferran Alet, Dylan Doblar, Allan Zhou, Josh Tenenbaum, Kenji Kawaguchi, Chelsea Finn:
Noether Networks: meta-learning useful conserved quantities. NeurIPS 2021: 16384-16397 - [c78]Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn:
Autonomous Reinforcement Learning via Subgoal Curricula. NeurIPS 2021: 18474-18486 - [c77]Guodong Zhang, Kyle Hsu, Jianing Li, Chelsea Finn, Roger B. Grosse:
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise. NeurIPS 2021: 19398-19410 - [c76]Marvin Zhang, Henrik Marklund, Nikita Dhawan, Abhishek Gupta, Sergey Levine, Chelsea Finn:
Adaptive Risk Minimization: Learning to Adapt to Domain Shift. NeurIPS 2021: 23664-23678 - [c75]Chris Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn:
Efficiently Identifying Task Groupings for Multi-Task Learning. NeurIPS 2021: 27503-27516 - [c74]Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn:
COMBO: Conservative Offline Model-Based Policy Optimization. NeurIPS 2021: 28954-28967 - [c73]Annie S. Chen, Suraj Nair, Chelsea Finn:
Learning Generalizable Robotic Reward Functions from "In-The-Wild" Human Videos. Robotics: Science and Systems 2021 - [i121]Julian Ibarz, Jie Tan, Chelsea Finn, Mrinal Kalakrishnan, Peter Pastor, Sergey Levine:
How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned. CoRR abs/2102.02915 (2021) - [i120]Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn:
COMBO: Conservative Offline Model-Based Policy Optimization. CoRR abs/2102.08363 (2021) - [i119]Ali Ghadirzadeh, Xi Chen, Petra Poklukar, Chelsea Finn, Mårten Björkman, Danica Kragic:
Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms. CoRR abs/2103.03697 (2021) - [i118]Bohan Wu, Suraj Nair, Roberto Martín-Martín, Li Fei-Fei, Chelsea Finn:
Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction. CoRR abs/2103.04174 (2021) - [i117]Behzad Haghgoo, Allan Zhou, Archit Sharma, Chelsea Finn:
Discriminator Augmented Model-Based Reinforcement Learning. CoRR abs/2103.12999 (2021) - [i116]Annie S. Chen, Suraj Nair, Chelsea Finn:
Learning Generalizable Robotic Reward Functions from "In-The-Wild" Human Videos. CoRR abs/2103.16817 (2021) - [i115]Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jake Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine:
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. CoRR abs/2104.07749 (2021) - [i114]Dmitry Kalashnikov, Jacob Varley, Yevgen Chebotar, Benjamin Swanson, Rico Jonschkowski, Chelsea Finn, Sergey Levine, Karol Hausman:
MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale. CoRR abs/2104.08212 (2021) - [i113]Huaxiu Yao, Linjun Zhang, Chelsea Finn:
Meta-Learning with Fewer Tasks through Task Interpolation. CoRR abs/2106.02695 (2021) - [i112]Mohammad Babaeizadeh, Mohammad Taghi Saffar, Suraj Nair, Sergey Levine, Chelsea Finn, Dumitru Erhan:
FitVid: Overfitting in Pixel-Level Video Prediction. CoRR abs/2106.13195 (2021) - [i111]Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn:
Visual Adversarial Imitation Learning using Variational Models. CoRR abs/2107.08829 (2021) - [i110]Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn:
Just Train Twice: Improving Group Robustness without Training Group Information. CoRR abs/2107.09044 (2021) - [i109]Guodong Zhang, Kyle Hsu, Jianing Li, Chelsea Finn, Roger B. Grosse:
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise. CoRR abs/2107.10211 (2021) - [i108]Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn:
Persistent Reinforcement Learning via Subgoal Curricula. CoRR abs/2107.12931 (2021) - [i107]John Willes, James Harrison, Ali Harakeh, Chelsea Finn, Marco Pavone, Steven Lake Waslander:
Bayesian Embeddings for Few-Shot Open World Recognition. CoRR abs/2107.13682 (2021) - [i106]Mike Wu, Noah D. Goodman, Chris Piech, Chelsea Finn:
ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback. CoRR abs/2107.14035 (2021) - [i105]Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.:
On the Opportunities and Risks of Foundation Models. CoRR abs/2108.07258 (2021) - [i104]Suraj Nair, Eric Mitchell, Kevin Chen, Brian Ichter, Silvio Savarese, Chelsea Finn:
Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation. CoRR abs/2109.01115 (2021) - [i103]Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn:
Efficiently Identifying Task Groupings for Multi-Task Learning. CoRR abs/2109.04617 (2021) - [i102]Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn:
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning. CoRR abs/2109.08128 (2021) - [i101]Annie Xie, Chelsea Finn:
Lifelong Robotic Reinforcement Learning by Retaining Experiences. CoRR abs/2109.09180 (2021) - [i100]Bohan Wu, Suraj Nair, Li Fei-Fei, Chelsea Finn:
Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks. CoRR abs/2109.10312 (2021) - [i99]Aviral Kumar, Anikait Singh, Stephen Tian, Chelsea Finn, Sergey Levine:
A Workflow for Offline Model-Free Robotic Reinforcement Learning. CoRR abs/2109.10813 (2021) - [i98]Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn,