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ORCIDChelsea Finn
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- affiliation: Stanford University, CA, USA
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2020 – today
- 2024
[j9]John Willes
, James Harrison, Ali Harakeh, Chelsea Finn, Marco Pavone, Steven L. Waslander:
Bayesian Embeddings for Few-Shot Open World Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 46(3): 1513-1529 (2024)- [j8]Caroline Choi, Fahim Tajwar, Yoonho Lee, Huaxiu Yao, Ananya Kumar, Chelsea Finn:
Conservative Prediction via Data-Driven Confidence Minimization. Trans. Mach. Learn. Res. 2024 (2024) - [c187]Ryan Park, Rafael Rafailov, Stefano Ermon, Chelsea Finn:
Disentangling Length from Quality in Direct Preference Optimization. ACL (Findings) 2024: 4998-5017 - [c186]Lukas Haas, Michal Skreta, Silas Alberti, Chelsea Finn:
PIGEON: Predicting Image Geolocations. CVPR 2024: 12893-12902 - [c185]Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Rich Walke, Chelsea Finn, Aviral Kumar, Sergey Levine:
Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models. ICLR 2024 - [c184]Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn:
Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features. ICLR 2024 - [c183]Jiayuan Gu, Sean Kirmani, Paul Wohlhart, Yao Lu, Montserrat Gonzalez Arenas, Kanishka Rao, Wenhao Yu, Chuyuan Fu, Keerthana Gopalakrishnan, Zhuo Xu, Priya Sundaresan, Peng Xu, Hao Su, Karol Hausman, Chelsea Finn, Quan Vuong, Ted Xiao:
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches. ICLR 2024 - [c182]Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh:
Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning. ICLR 2024 - [c181]Eric Mitchell, Rafael Rafailov, Archit Sharma, Chelsea Finn, Christopher D. Manning:
An Emulator for Fine-tuning Large Language Models using Small Language Models. ICLR 2024 - [c180]Charlotte Nicks, Eric Mitchell, Rafael Rafailov, Archit Sharma, Christopher D. Manning, Chelsea Finn, Stefano Ermon:
Language Model Detectors Are Easily Optimized Against. ICLR 2024 - [c179]Katherine Tian, Eric Mitchell, Huaxiu Yao, Christopher D. Manning, Chelsea Finn:
Fine-Tuning Language Models for Factuality. ICLR 2024 - [c178]Johnathan Xie, Yoonho Lee, Annie S. Chen, Chelsea Finn:
Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning. ICLR 2024 - [c177]Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn:
Improving Domain Generalization with Domain Relations. ICLR 2024 - [c176]Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao:
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. ICLR 2024 - [c175]Kyle Hsu, Jubayer Ibn Hamid, Kaylee Burns, Chelsea Finn, Jiajun Wu:
Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning. ICML 2024 - [c174]Soroush Nasiriany, Fei Xia, Wenhao Yu, Ted Xiao, Jacky Liang, Ishita Dasgupta, Annie Xie, Danny Driess, Ayzaan Wahid, Zhuo Xu, Quan Vuong, Tingnan Zhang, Tsang-Wei Edward Lee, Kuang-Huei Lee, Peng Xu, Sean Kirmani, Yuke Zhu, Andy Zeng, Karol Hausman, Nicolas Heess, Chelsea Finn, Sergey Levine, Brian Ichter:
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. ICML 2024 - [c173]Moritz Stephan, Alexander Khazatsky, Eric Mitchell, Annie S. Chen, Sheryl Hsu, Archit Sharma, Chelsea Finn:
RLVF: Learning from Verbal Feedback without Overgeneralization. ICML 2024 - [c172]Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar:
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data. ICML 2024 - [c171]Annie Xie, Logan M. Bhamidipaty, Evan Zheran Liu, Joey Hong, Sergey Levine, Chelsea Finn:
Learning to Explore in POMDPs with Informational Rewards. ICML 2024 - [c170]Annie Xie, Lisa Lee, Ted Xiao, Chelsea Finn:
Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation. ICRA 2024: 3153-3160 - [c169]Jingyun Yang, Max Sobol Mark, Brandon Vu, Archit Sharma, Jeannette Bohg, Chelsea Finn:
Robot Fine-Tuning Made Easy: Pre-Training Rewards and Policies for Autonomous Real-World Reinforcement Learning. ICRA 2024: 4804-4811 - [c168]Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin:
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. ICRA 2024: 6892-6903 - [c167]Jianlan Luo, Zheyuan Hu, Charles Xu, You Liang Tan, Jacob Berg, Archit Sharma, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine:
SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning. ICRA 2024: 16961-16969 - [c166]Victor Kolev, Rafael Rafailov, Kyle Hatch, Jiajun Wu, Chelsea Finn:
Efficient imitation learning with conservative world models. L4DC 2024: 1777-1790 - [c165]Evan Zheran Liu, David Yuan, Ahmed Ahmed, Elyse Cornwall, Juliette Woodrow, Kaylee Burns, Allen Nie, Emma Brunskill, Chris Piech, Chelsea Finn:
A Fast and Accurate Machine Learning Autograder for the Breakout Assignment. SIGCSE (1) 2024: 736-742 - [c164]Yoonho Lee, Michelle S. Lam, Helena Vasconcelos, Michael S. Bernstein, Chelsea Finn:
Clarify: Improving Model Robustness With Natural Language Corrections. UIST 2024: 133:1-133:19 - [i237]Zipeng Fu, Tony Z. Zhao, Chelsea Finn:
Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation. CoRR abs/2401.02117 (2024) - [i236]Rafael Rafailov, Kyle Hatch, Victor Kolev, John D. Martin, Mariano Phielipp, Chelsea Finn:
MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning. CoRR abs/2401.03306 (2024) - [i235]Caroline Choi, Yoonho Lee, Annie S. Chen, Allan Zhou, Aditi Raghunathan, Chelsea Finn:
AutoFT: Robust Fine-Tuning by Optimizing Hyperparameters on OOD Data. CoRR abs/2401.10220 (2024) - [i234]Michael Ahn, Debidatta Dwibedi, Chelsea Finn, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Karol Hausman, Brian Ichter, Alex Irpan, Nikhil J. Joshi, Ryan Julian, Sean Kirmani, Isabel Leal, Tsang-Wei Edward Lee, Sergey Levine, Yao Lu, Sharath Maddineni, Kanishka Rao, Dorsa Sadigh, Pannag Sanketi, Pierre Sermanet, Quan Vuong, Stefan Welker, Fei Xia, Ted Xiao, Peng Xu, Steve Xu, Zhuo Xu:
AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents. CoRR abs/2401.12963 (2024) - [i233]Jianlan Luo, Zheyuan Hu, Charles Xu, You Liang Tan, Jacob Berg, Archit Sharma, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine:
SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning. CoRR abs/2401.16013 (2024) - [i232]Yoonho Lee, Michelle S. Lam, Helena Vasconcelos, Michael S. Bernstein, Chelsea Finn:
Clarify: Improving Model Robustness With Natural Language Corrections. CoRR abs/2402.03715 (2024) - [i231]Allan Zhou, Chelsea Finn, James Harrison:
Universal Neural Functionals. CoRR abs/2402.05232 (2024) - [i230]Soroush Nasiriany, Fei Xia, Wenhao Yu, Ted Xiao, Jacky Liang, Ishita Dasgupta, Annie Xie, Danny Driess, Ayzaan Wahid, Zhuo Xu, Quan Vuong, Tingnan Zhang, Tsang-Wei Edward Lee, Kuang-Huei Lee, Peng Xu, Sean Kirmani, Yuke Zhu, Andy Zeng, Karol Hausman, Nicolas Heess, Chelsea Finn, Sergey Levine, Brian Ichter:
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. CoRR abs/2402.07872 (2024) - [i229]Moritz Stephan, Alexander Khazatsky, Eric Mitchell, Annie S. Chen, Sheryl Hsu, Archit Sharma, Chelsea Finn:
RLVF: Learning from Verbal Feedback without Overgeneralization. CoRR abs/2402.10893 (2024) - [i228]Yiyang Zhou, Chenhang Cui, Rafael Rafailov, Chelsea Finn, Huaxiu Yao:
Aligning Modalities in Vision Large Language Models via Preference Fine-tuning. CoRR abs/2402.11411 (2024) - [i227]Archit Sharma, Sedrick Keh, Eric Mitchell, Chelsea Finn, Kushal Arora, Thomas Kollar:
A Critical Evaluation of AI Feedback for Aligning Large Language Models. CoRR abs/2402.12366 (2024) - [i226]Johnathan Xie, Yoonho Lee, Annie S. Chen, Chelsea Finn:
Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning. CoRR abs/2402.14789 (2024) - [i225]Jonathan Yang, Catherine Glossop, Arjun Bhorkar, Dhruv Shah, Quan Vuong, Chelsea Finn, Dorsa Sadigh, Sergey Levine:
Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation. CoRR abs/2402.19432 (2024) - [i224]Jensen Gao, Annie Xie, Ted Xiao, Chelsea Finn, Dorsa Sadigh:
Efficient Data Collection for Robotic Manipulation via Compositional Generalization. CoRR abs/2403.05110 (2024) - [i223]Lucy Xiaoyang Shi, Zheyuan Hu, Tony Z. Zhao, Archit Sharma, Karl Pertsch, Jianlan Luo, Sergey Levine, Chelsea Finn:
Yell At Your Robot: Improving On-the-Fly from Language Corrections. CoRR abs/2403.12910 (2024) - [i222]Ryan Park, Rafael Rafailov, Stefano Ermon, Chelsea Finn:
Disentangling Length from Quality in Direct Preference Optimization. CoRR abs/2403.19159 (2024) - [i221]Kyle Hsu, Jubayer Ibn Hamid, Kaylee Burns, Chelsea Finn, Jiajun Wu:
Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning. CoRR abs/2404.10282 (2024) - [i220]Rafael Rafailov, Joey Hejna, Ryan Park, Chelsea Finn:
From r to Q*: Your Language Model is Secretly a Q-Function. CoRR abs/2404.12358 (2024) - [i219]Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar:
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data. CoRR abs/2404.14367 (2024) - [i218]ALOHA 2 Team, Jorge Aldaco, Travis Armstrong, Robert Baruch, Jeff Bingham, Sanky Chan, Kenneth Draper, Debidatta Dwibedi, Chelsea Finn, Pete Florence, Spencer Goodrich, Wayne Gramlich, Torr Hage, Alexander Herzog, Jonathan Hoech, Thinh Nguyen, Ian Storz, Baruch Tabanpour, Leila Takayama, Jonathan Tompson, Ayzaan Wahid, Ted Wahrburg, Sichun Xu, Sergey Yaroshenko, Kevin Zakka, Tony Z. Zhao:
ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperation. CoRR abs/2405.02292 (2024) - [i217]Xuanlin Li, Kyle Hsu, Jiayuan Gu, Karl Pertsch, Oier Mees, Homer Rich Walke, Chuyuan Fu, Ishikaa Lunawat, Isabel Sieh, Sean Kirmani, Sergey Levine, Jiajun Wu, Chelsea Finn, Hao Su, Quan Vuong, Ted Xiao:
Evaluating Real-World Robot Manipulation Policies in Simulation. CoRR abs/2405.05941 (2024) - [i216]Octo Model Team, Dibya Ghosh, Homer Walke, Karl Pertsch, Kevin Black, Oier Mees, Sudeep Dasari, Joey Hejna, Tobias Kreiman, Charles Xu, Jianlan Luo, You Liang Tan, Lawrence Yunliang Chen, Pannag Sanketi, Quan Vuong, Ted Xiao, Dorsa Sadigh, Chelsea Finn, Sergey Levine:
Octo: An Open-Source Generalist Robot Policy. CoRR abs/2405.12213 (2024) - [i215]Victor Kolev, Rafael Rafailov, Kyle Hatch, Jiajun Wu, Chelsea Finn:
Efficient Imitation Learning with Conservative World Models. CoRR abs/2405.13193 (2024) - [i214]Rafael Rafailov, Yaswanth Chittepu, Ryan Park, Harshit Sikchi, Joey Hejna, W. Bradley Knox, Chelsea Finn, Scott Niekum:
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms. CoRR abs/2406.02900 (2024) - [i213]Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan Paul Foster, Grace Lam, Pannag Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, Chelsea Finn:
OpenVLA: An Open-Source Vision-Language-Action Model. CoRR abs/2406.09246 (2024) - [i212]Zipeng Fu, Qingqing Zhao, Qi Wu, Gordon Wetzstein, Chelsea Finn:
HumanPlus: Humanoid Shadowing and Imitation from Humans. CoRR abs/2406.10454 (2024) - [i211]Maximilian Du, Alexander Khazatsky, Tobias Gerstenberg, Chelsea Finn:
To Err is Robotic: Rapid Value-Based Trial-and-Error during Deployment. CoRR abs/2406.15917 (2024) - [i210]Annie S. Chen, Alec M. Lessing, Andy Tang, Govind Chada, Laura M. Smith, Sergey Levine, Chelsea Finn:
Commonsense Reasoning for Legged Robot Adaptation with Vision-Language Models. CoRR abs/2407.02666 (2024) - [i209]Zhaorun Chen, Yichao Du, Zichen Wen, Yiyang Zhou, Chenhang Cui, Zhenzhen Weng, Haoqin Tu, Chaoqi Wang, Zhengwei Tong, Qinglan Huang, Canyu Chen, Qinghao Ye, Zhihong Zhu, Yuqing Zhang, Jiawei Zhou, Zhuokai Zhao, Rafael Rafailov, Chelsea Finn, Huaxiu Yao:
MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation? CoRR abs/2407.04842 (2024) - [i208]Hao-Tien Lewis Chiang, Zhuo Xu, Zipeng Fu, Mithun George Jacob, Tingnan Zhang, Tsang-Wei Edward Lee, Wenhao Yu, Connor Schenck, David Rendleman, Dhruv Shah, Fei Xia, Jasmine Hsu, Jonathan Hoech, Pete Florence, Sean Kirmani, Sumeet Singh, Vikas Sindhwani, Carolina Parada, Chelsea Finn, Peng Xu, Sergey Levine, Jie Tan:
Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs. CoRR abs/2407.07775 (2024) - [i207]Michal Zawalski, William Chen, Karl Pertsch, Oier Mees, Chelsea Finn, Sergey Levine:
Robotic Control via Embodied Chain-of-Thought Reasoning. CoRR abs/2407.08693 (2024) - [i206]Olivia Y. Lee, Annie Xie, Kuan Fang, Karl Pertsch, Chelsea Finn:
Affordance-Guided Reinforcement Learning via Visual Prompting. CoRR abs/2407.10341 (2024) - [i205]Ji Woong Kim, Tony Z. Zhao, Samuel Schmidgall, Anton Deguet, Marin Kobilarov, Chelsea Finn, Axel Krieger:
Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks. CoRR abs/2407.12998 (2024) - [i204]Louis Castricato, Nathan Lile, Rafael Rafailov, Jan-Philipp Fränken, Chelsea Finn:
PERSONA: A Reproducible Testbed for Pluralistic Alignment. CoRR abs/2407.17387 (2024) - [i203]Pranav Putta, Edmund Mills, Naman Garg, Sumeet Motwani, Chelsea Finn, Divyansh Garg, Rafael Rafailov:
Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents. CoRR abs/2408.07199 (2024) - [i202]Rafael Rafailov, Kyle Hatch, Anikait Singh, Laura M. Smith, Aviral Kumar, Ilya Kostrikov, Philippe Hansen-Estruch, Victor Kolev, Philip J. Ball, Jiajun Wu, Chelsea Finn, Sergey Levine:
D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning. CoRR abs/2408.08441 (2024) - [i201]Yuejiang Liu, Jubayer Ibn Hamid, Annie Xie, Yoonho Lee, Maximilian Du, Chelsea Finn:
Bidirectional Decoding: Improving Action Chunking via Closed-Loop Resampling. CoRR abs/2408.17355 (2024) - [i200]Johnathan Xie, Annie S. Chen, Yoonho Lee, Eric Mitchell, Chelsea Finn:
Calibrating Language Models with Adaptive Temperature Scaling. CoRR abs/2409.19817 (2024) - [i199]Qi Wu, Zipeng Fu, Xuxin Cheng, Xiaolong Wang, Chelsea Finn:
Helpful DoggyBot: Open-World Object Fetching using Legged Robots and Vision-Language Models. CoRR abs/2410.00231 (2024) - 2023
- [j7]Xinyu Yang, Huaxiu Yao, Allan Zhou, Chelsea Finn:
Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations. Trans. Mach. Learn. Res. 2023 (2023) - [c163]Peter Henderson, Eric Mitchell, Christopher D. Manning, Dan Jurafsky, Chelsea Finn:
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models. AIES 2023: 287-296 - [c162]Ziwen Zhuang, Zipeng Fu, Jianren Wang, Christopher G. Atkeson, Sören Schwertfeger, Chelsea Finn, Hang Zhao:
Robot Parkour Learning. CoRL 2023: 73-92 - [c161]Homer Rich Walke, Kevin Black, Tony Z. Zhao, Quan Vuong, Chongyi Zheng, Philippe Hansen-Estruch, Andre Wang He, Vivek Myers, Moo Jin Kim, Max Du, Abraham Lee, Kuan Fang, Chelsea Finn, Sergey Levine:
BridgeData V2: A Dataset for Robot Learning at Scale. CoRL 2023: 1723-1736 - [c160]Brianna Zitkovich, Tianhe Yu, Sichun Xu, Peng Xu, Ted Xiao, Fei Xia, Jialin Wu, Paul Wohlhart, Stefan Welker, Ayzaan Wahid, Quan Vuong, Vincent Vanhoucke, Huong T. Tran, Radu Soricut, Anikait Singh, Jaspiar Singh, Pierre Sermanet, Pannag R. Sanketi, Grecia Salazar, Michael S. Ryoo, Krista Reymann, Kanishka Rao, Karl Pertsch, Igor Mordatch, Henryk Michalewski, Yao Lu, Sergey Levine, Lisa Lee, Tsang-Wei Edward Lee, Isabel Leal, Yuheng Kuang, Dmitry Kalashnikov, Ryan Julian, Nikhil J. Joshi, Alex Irpan, Brian Ichter, Jasmine Hsu, Alexander Herzog, Karol Hausman, Keerthana Gopalakrishnan, Chuyuan Fu, Pete Florence, Chelsea Finn, Kumar Avinava Dubey, Danny Driess, Tianli Ding, Krzysztof Marcin Choromanski, Xi Chen, Yevgen Chebotar, Justice Carbajal, Noah Brown, Anthony Brohan, Montserrat Gonzalez Arenas, Kehang Han:
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRL 2023: 2165-2183 - [c159]Lucy Xiaoyang Shi, Archit Sharma, Tony Z. Zhao, Chelsea Finn:
Waypoint-Based Imitation Learning for Robotic Manipulation. CoRL 2023: 2195-2209 - [c158]Jonathan Heewon Yang, Dorsa Sadigh, Chelsea Finn:
Polybot: Training One Policy Across Robots While Embracing Variability. CoRL 2023: 2955-2974 - [c157]Archit Sharma, Ahmed M. Ahmed, Rehaan Ahmad, Chelsea Finn:
Self-Improving Robots: End-to-End Autonomous Visuomotor Reinforcement Learning. CoRL 2023: 3292-3308 - [c156]Austin Stone, Ted Xiao, Yao Lu, Keerthana Gopalakrishnan, Kuang-Huei Lee, Quan Vuong, Paul Wohlhart, Sean Kirmani, Brianna Zitkovich, Fei Xia, Chelsea Finn, Karol Hausman:
Open-World Object Manipulation using Pre-Trained Vision-Language Models. CoRL 2023: 3397-3417 - [c155]Rafael Rafailov, Kyle Beltran Hatch, Victor Kolev, John D. Martin, Mariano Phielipp, Chelsea Finn:
MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning. CoRL 2023: 3654-3671 - [c154]Yevgen Chebotar, Quan Vuong, Karol Hausman, Fei Xia, Yao Lu, Alex Irpan, Aviral Kumar, Tianhe Yu, Alexander Herzog, Karl Pertsch, Keerthana Gopalakrishnan, Julian Ibarz, Ofir Nachum, Sumedh Anand Sontakke, Grecia Salazar, Huong T. Tran, Jodilyn Peralta, Clayton Tan, Deeksha Manjunath, Jaspiar Singh, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, Sergey Levine:
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. CoRL 2023: 3909-3928 - [c153]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. CVPR 2023: 17907-17917 - [c152]Nathan Hu, Eric Mitchell, Christopher D. Manning, Chelsea Finn:
Meta-Learning Online Adaptation of Language Models. EMNLP 2023: 4418-4432 - [c151]Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, Christopher D. Manning:
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback. EMNLP 2023: 5433-5442 - [c150]Yoonho Lee, Annie S. Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, Chelsea Finn:
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts. ICLR 2023 - [c149]Yoonho Lee, Huaxiu Yao, Chelsea Finn:
Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement. ICLR 2023 - [c148]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. ICLR 2023 - [c147]Stephen Tian, Chelsea Finn, Jiajun Wu:
A Control-Centric Benchmark for Video Prediction. ICLR 2023 - [c146]Evan Zheran Liu, Sahaana Suri, Tong Mu, Allan Zhou, Chelsea Finn:
Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning. ICML 2023: 21997-22008 - [c145]Eric Mitchell, Yoonho Lee, Alexander Khazatsky, Christopher D. Manning, Chelsea Finn:
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature. ICML 2023: 24950-24962 - [c144]Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta:
Train Offline, Test Online: A Real Robot Learning Benchmark. ICRA 2023: 9197-9203 - [c143]Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn:
Contrastive Example-Based Control. L4DC 2023: 155-169 - [c142]Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill:
Supervised Pretraining Can Learn In-Context Reinforcement Learning. NeurIPS 2023 - [c141]Kyle Hsu, William Dorrell, James C. R. Whittington, Jiajun Wu, Chelsea Finn:
Disentanglement via Latent Quantization. NeurIPS 2023 - [c140]Mitsuhiko Nakamoto, Simon 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. NeurIPS 2023 - [c139]Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D. Manning, Stefano Ermon, Chelsea Finn:
Direct Preference Optimization: Your Language Model is Secretly a Reward Model. NeurIPS 2023 - [c138]Sumedh Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti:
RoboCLIP: One Demonstration is Enough to Learn Robot Policies. NeurIPS 2023 - [c137]Allan Zhou, Kaien Yang, Kaylee Burns, Adriano Cardace, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn:
Permutation Equivariant Neural Functionals. NeurIPS 2023 - [c136]Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn:
Neural Functional Transformers. NeurIPS 2023 - [c135]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 R. Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong T. 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. Robotics: Science and Systems 2023 - [c134]Maximilian Du, Suraj Nair, Dorsa Sadigh, Chelsea Finn:
Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets. Robotics: Science and Systems 2023 - [c133]Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang:
Language-Driven Representation Learning for Robotics. Robotics: Science and Systems 2023 - [c132]Aviral Kumar, Anikait Singh, Frederik D. Ebert, Mitsuhiko Nakamoto, Yanlai Yang, Chelsea Finn, Sergey Levine:
Pre-Training for Robots: Offline RL Enables Learning New Tasks in a Handful of Trials. Robotics: Science and Systems 2023 - [c131]Tony Z. Zhao, Vikash Kumar, Sergey Levine, Chelsea Finn:
Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware. Robotics: Science and Systems 2023 - [i198]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) - [i197]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) - [i196]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) - [i195]Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn:
Leveraging Domain Relations for Domain Generalization. CoRR abs/2302.02609 (2023) - [i194]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) - [i193]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) - [i192]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) - [i191]Allan Zhou, Kaien Yang, Kaylee Burns, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn:
Permutation Equivariant Neural Functionals. CoRR abs/2302.14040 (2023) - [i190]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) - [i189]Archit Sharma, Ahmed M. Ahmed, Rehaan Ahmad, Chelsea Finn:
Self-Improving Robots: End-to-End Autonomous Visuomotor Reinforcement Learning. CoRR abs/2303.01488 (2023) - [i188]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) - [i187]Maximilian Du, Suraj Nair, Dorsa Sadigh, Chelsea Finn:
Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets. CoRR abs/2304.08742 (2023) - [i186]Tony Z. Zhao, Vikash Kumar, Sergey Levine, Chelsea Finn:
Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware. CoRR abs/2304.13705 (2023) - [i185]Stephen Tian, Chelsea Finn, Jiajun Wu:
A Control-Centric Benchmark for Video Prediction. CoRR abs/2304.13723 (2023) - [i184]Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn:
Neural Functional Transformers. CoRR abs/2305.13546 (2023) - [i183]Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, Christopher D. Manning:
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback. CoRR abs/2305.14975 (2023) - [i182]Nathan Hu, Eric Mitchell, Christopher D. Manning, Chelsea Finn:
Meta-Learning Online Adaptation of Language Models. CoRR abs/2305.15076 (2023) - [i181]Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D. Manning, Chelsea Finn:
Direct Preference Optimization: Your Language Model is Secretly a Reward Model. CoRR abs/2305.18290 (2023) - [i180]Kyle Hsu, Will Dorrell, James C. R. Whittington, Jiajun Wu, Chelsea Finn:
Disentanglement via Latent Quantization. CoRR abs/2305.18378 (2023) - [i179]Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta:
Train Offline, Test Online: A Real Robot Learning Benchmark. CoRR abs/2306.00942 (2023) - [i178]Caroline Choi, Fahim Tajwar, Yoonho Lee, Huaxiu Yao, Ananya Kumar, Chelsea Finn:
Conservative Prediction via Data-Driven Confidence Minimization. CoRR abs/2306.04974 (2023) - [i177]Evan Zheran Liu, Sahaana Suri, Tong Mu, Allan Zhou, Chelsea Finn:
Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning. CoRR abs/2306.08400 (2023) - [i176]Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn:
Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts. CoRR abs/2306.11120 (2023) - [i175]Jonathan N. Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill:
Supervised Pretraining Can Learn In-Context Reinforcement Learning. CoRR abs/2306.14892 (2023) - [i174]Annie Xie, Lisa Lee, Ted Xiao, Chelsea Finn:
Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation. CoRR abs/2307.03659 (2023) - [i173]Jonathan Heewon Yang, Dorsa Sadigh, Chelsea Finn:
Polybot: Training One Policy Across Robots While Embracing Variability. CoRR abs/2307.03719 (2023) - [i172]Moo Jin Kim, Jiajun Wu, Chelsea Finn:
Giving Robots a Hand: Learning Generalizable Manipulation with Eye-in-Hand Human Video Demonstrations. CoRR abs/2307.05959 (2023) - [i171]Kyle Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn:
Contrastive Example-Based Control. CoRR abs/2307.13101 (2023) - [i170]Lucy Xiaoyang Shi, Archit Sharma, Tony Z. Zhao, Chelsea Finn:
Waypoint-Based Imitation Learning for Robotic Manipulation. CoRR abs/2307.14326 (2023) - [i169]Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Xi Chen, Krzysztof Choromanski, Tianli Ding, Danny Driess, Avinava Dubey, Chelsea Finn, Pete Florence, Chuyuan Fu, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Kehang Han, Karol Hausman, Alexander Herzog, Jasmine Hsu, Brian Ichter, Alex Irpan, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Lisa Lee, Tsang-Wei Edward Lee, Sergey Levine, Yao Lu, Henryk Michalewski, Igor Mordatch, Karl Pertsch, Kanishka Rao, Krista Reymann, Michael S. Ryoo, Grecia Salazar, Pannag Sanketi, Pierre Sermanet, Jaspiar Singh, Anikait Singh, Radu Soricut, Huong T. Tran, Vincent Vanhoucke, Quan Vuong, Ayzaan Wahid, Stefan Welker, Paul Wohlhart, Jialin Wu, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich:
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRR abs/2307.15818 (2023) - [i168]Homer Walke, Kevin Black, Abraham Lee, Moo Jin Kim, Maximilian Du, Chongyi Zheng, Tony Z. Zhao, Philippe Hansen-Estruch, Quan Vuong, Andre He, Vivek Myers, Kuan Fang, Chelsea Finn, Sergey Levine:
BridgeData V2: A Dataset for Robot Learning at Scale. CoRR abs/2308.12952 (2023) - [i167]Ziwen Zhuang, Zipeng Fu, Jianren Wang, Christopher G. Atkeson, Sören Schwertfeger, Chelsea Finn, Hang Zhao:
Robot Parkour Learning. CoRR abs/2309.05665 (2023) - [i166]Yevgen Chebotar, Quan Vuong, Alex Irpan, Karol Hausman, Fei Xia, Yao Lu, Aviral Kumar, Tianhe Yu, Alexander Herzog, Karl Pertsch, Keerthana Gopalakrishnan, Julian Ibarz, Ofir Nachum, Sumedh Sontakke, Grecia Salazar, Huong T. Tran, Jodilyn Peralta, Clayton Tan, Deeksha Manjunath, Jaspiar Singh, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, Sergey Levine:
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. CoRR abs/2309.10150 (2023) - [i165]Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao:
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. CoRR abs/2310.00754 (2023) - [i164]Sumedh A. Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti:
RoboCLIP: One Demonstration is Enough to Learn Robot Policies. CoRR abs/2310.07899 (2023) - [i163]Max Sobol Mark, Archit Sharma, Fahim Tajwar, Rafael Rafailov, Sergey Levine, Chelsea Finn:
Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias. CoRR abs/2310.08558 (2023) - [i162]Open X.-Embodiment Collaboration, Abhishek Padalkar, Acorn Pooley, Ajinkya Jain, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Raj, Anikait Singh, Anthony Brohan, Antonin Raffin, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Brian Ichter, Cewu Lu, Charles Xu, Chelsea Finn, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Chuer Pan, Chuyuan Fu, Coline Devin, Danny Driess, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Federico Ceola, Fei Xia, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Giulio Schiavi, Gregory Kahn, Hao Su, Haoshu Fang, Haochen Shi, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Igor Mordatch, Ilija Radosavovic, et al.:
Open X-Embodiment: Robotic Learning Datasets and RT-X Models. CoRR abs/2310.08864 (2023) - [i161]Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Walke, Chelsea Finn, Aviral Kumar, Sergey Levine:
Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models. CoRR abs/2310.10639 (2023) - [i160]Eric Mitchell, Rafael Rafailov, Archit Sharma, Chelsea Finn, Christopher D. Manning:
An Emulator for Fine-Tuning Large Language Models using Small Language Models. CoRR abs/2310.12962 (2023) - [i159]Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh:
Contrastive Preference Learning: Learning from Human Feedback without RL. CoRR abs/2310.13639 (2023) - [i158]Jingyun Yang, Max Sobol Mark, Brandon Vu, Archit Sharma, Jeannette Bohg, Chelsea Finn:
Robot Fine-Tuning Made Easy: Pre-Training Rewards and Policies for Autonomous Real-World Reinforcement Learning. CoRR abs/2310.15145 (2023) - [i157]Annie S. Chen, Govind Chada, Laura M. Smith, Archit Sharma, Zipeng Fu, Sergey Levine, Chelsea Finn:
Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment. CoRR abs/2311.01059 (2023) - [i156]Jiayuan Gu, Sean Kirmani, Paul Wohlhart, Yao Lu, Montserrat Gonzalez Arenas, Kanishka Rao, Wenhao Yu, Chuyuan Fu, Keerthana Gopalakrishnan, Zhuo Xu, Priya Sundaresan, Peng Xu, Hao Su, Karol Hausman, Chelsea Finn, Quan Vuong, Ted Xiao:
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches. CoRR abs/2311.01977 (2023) - [i155]Katherine Tian, Eric Mitchell, Huaxiu Yao, Christopher D. Manning, Chelsea Finn:
Fine-tuning Language Models for Factuality. CoRR abs/2311.08401 (2023) - [i154]Kaylee Burns, Zach Witzel, Jubayer Ibn Hamid, Tianhe Yu, Chelsea Finn, Karol Hausman:
What Makes Pre-Trained Visual Representations Successful for Robust Manipulation? CoRR abs/2312.12444 (2023) - 2022
- [j6]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. J. Mach. Learn. Res. 23: 174:1-174:37 (2022) - [c130]Annie Xie, Chelsea Finn:
Lifelong Robotic Reinforcement Learning by Retaining Experiences. CoLLAs 2022: 838-855 - [c129]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 - [c128]Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, Abhinav Gupta:
R3M: A Universal Visual Representation for Robot Manipulation. CoRL 2022: 892-909 - [c127]Kaylee Burns, Tianhe Yu, Chelsea Finn, Karol Hausman:
Offline Reinforcement Learning at Multiple Frequencies. CoRL 2022: 2041-2051 - [c126]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 - [c125]Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, Sergey Levine:
CoMPS: Continual Meta Policy Search. ICLR 2022 - [c124]Kyle Hsu, Moo Jin Kim, Rafael Rafailov, Jiajun Wu, Chelsea Finn:
Vision-Based Manipulators Need to Also See from Their Hands. ICLR 2022 - [c123]Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, Christopher D. Manning:
Fast Model Editing at Scale. ICLR 2022 - [c122]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 - [c121]Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn:
Autonomous Reinforcement Learning: Formalism and Benchmarking. ICLR 2022 - [c120]Huaxiu Yao, Linjun Zhang, Chelsea Finn:
Meta-Learning with Fewer Tasks through Task Interpolation. ICLR 2022 - [c119]Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn:
Do deep networks transfer invariances across classes? ICLR 2022 - [c118]Eric Mitchell, Charles Lin, Antoine Bosselut, Christopher D. Manning, Chelsea Finn:
Memory-Based Model Editing at Scale. ICML 2022: 15817-15831 - [c117]Archit Sharma, Rehaan Ahmad, Chelsea Finn:
A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning. ICML 2022: 19645-19657 - [c116]Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang:
Robust Policy Learning over Multiple Uncertainty Sets. ICML 2022: 24414-24429 - [c115]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 - [c114]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 - [c113]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 - [c112]Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Jianhao Wang, Alex Yuan Gao, Wenzhe Li, Liang Bin, Chelsea Finn, Chongjie Zhang:
LAPO: Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning. NeurIPS 2022 - [c111]Annie S. Chen, Archit Sharma, Sergey Levine, Chelsea Finn:
You Only Live Once: Single-Life Reinforcement Learning. NeurIPS 2022 - [c110]Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn:
Learning Options via Compression. NeurIPS 2022 - [c109]Evan Zheran Liu, Moritz Stephan, Allen Nie, Chris Piech, Emma Brunskill, Chelsea Finn:
Giving Feedback on Interactive Student Programs with Meta-Exploration. NeurIPS 2022 - [c108]Annie Xie, Fahim Tajwar, Archit Sharma, Chelsea Finn:
When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning. NeurIPS 2022 - [c107]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. NeurIPS 2022 - [c106]Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y. Zou, Chelsea Finn:
C-Mixup: Improving Generalization in Regression. NeurIPS 2022 - [c105]Marvin Zhang, Sergey Levine, Chelsea Finn:
MEMO: Test Time Robustness via Adaptation and Augmentation. NeurIPS 2022 - [c104]Maximilian Du, Olivia Y. Lee, Suraj Nair, Chelsea Finn:
Play it by Ear: Learning Skills amidst Occlusion through Audio-Visual Imitation Learning. Robotics: Science and Systems 2022 - [c103]Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, Sergey Levine:
Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets. Robotics: Science and Systems 2022 - [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 T. 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, Sergey Levine:
Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets. CoRR abs/2109.13396 (2021) - [i97]Marvin Zhang, Sergey Levine, Chelsea Finn:
MEMO: Test Time Robustness via Adaptation and Augmentation. CoRR abs/2110.09506 (2021) - [i96]Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, Christopher D. Manning:
Fast Model Editing at Scale. CoRR abs/2110.11309 (2021) - [i95]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. CoRR abs/2110.14057 (2021) - [i94]Ferran Alet, Dylan Doblar, Allan Zhou, Joshua B. Tenenbaum, Kenji Kawaguchi, Chelsea Finn:
Noether Networks: Meta-Learning Useful Conserved Quantities. CoRR abs/2112.03321 (2021) - [i93]Michael Luo, Ashwin Balakrishna, Brijen Thananjeyan, Suraj Nair, Julian Ibarz, Jie Tan, Chelsea Finn, Ion Stoica, Ken Goldberg:
MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance. CoRR abs/2112.03575 (2021) - [i92]Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D. Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine:
Information is Power: Intrinsic Control via Information Capture. CoRR abs/2112.03899 (2021) - [i91]Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, Sergey Levine:
CoMPS: Continual Meta Policy Search. CoRR abs/2112.04467 (2021) - [i90]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. CoRR abs/2112.05090 (2021) - [i89]Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn:
Autonomous Reinforcement Learning: Formalism and Benchmarking. CoRR abs/2112.09605 (2021) - 2020
- [c72]Mark Woodward, Chelsea Finn, Karol Hausman:
Learning to Interactively Learn and Assist. AAAI 2020: 2535-2543 - [c71]Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn:
Reinforcement Learning with Videos: Combining Offline Observations with Interaction. CoRL 2020: 339-354 - [c70]Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh:
Learning Latent Representations to Influence Multi-Agent Interaction. CoRL 2020: 575-588 - [c69]Zihao Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine:
MELD: Meta-Reinforcement Learning from Images via Latent State Models. CoRL 2020: 1246-1261 - [c68]Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman:
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning. CoRL 2020: 2120-2136 - [c67]Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine, Chelsea Finn:
Learning Predictive Models from Observation and Interaction. ECCV (20) 2020: 708-725 - [c66]Lukasz Kaiser, Mohammad Babaeizadeh, Piotr Milos, Blazej Osinski, Roy H. Campbell, Konrad Czechowski, Dumitru Erhan, Chelsea Finn, Piotr Kozakowski, Sergey Levine, Afroz Mohiuddin, Ryan Sepassi, George Tucker, Henryk Michalewski:
Model Based Reinforcement Learning for Atari. ICLR 2020 - [c65]Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma:
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation. ICLR 2020 - [c64]Suraj Nair, Chelsea Finn:
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation. ICLR 2020 - [c63]Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn:
Meta-Learning without Memorization. ICLR 2020 - [c62]Allan Zhou, Eric Jang, Daniel Kappler, Alexander Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn:
Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards. ICLR 2020 - [c61]Kefan Dong, Yuping Luo, Tianhe Yu, Chelsea Finn, Tengyu Ma:
On the Expressivity of Neural Networks for Deep Reinforcement Learning. ICML 2020: 2627-2637 - [c60]Suraj Nair, Silvio Savarese, Chelsea Finn:
Goal-Aware Prediction: Learning to Model What Matters. ICML 2020: 7207-7219 - [c59]Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman:
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings. ICML 2020: 11055-11065 - [c58]Suraj Nair, Mohammad Babaeizadeh, Chelsea Finn, Sergey Levine, Vikash Kumar:
TRASS: Time Reversal as Self-Supervision. ICRA 2020: 115-121 - [c57]Akhil Padmanabha, Frederik Ebert, Stephen Tian, Roberto Calandra, Chelsea Finn, Sergey Levine:
OmniTact: A Multi-Directional High-Resolution Touch Sensor. ICRA 2020: 618-624 - [c56]Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn:
Scalable Multi-Task Imitation Learning with Autonomous Improvement. ICRA 2020: 2167-2173 - [c55]Xingyou Song, Yuxiang Yang, Krzysztof Choromanski, Ken Caluwaerts, Wenbo Gao, Chelsea Finn, Jie Tan:
Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning. IROS 2020: 3769-3776 - [c54]James Harrison, Apoorva Sharma, Chelsea Finn, Marco Pavone:
Continuous Meta-Learning without Tasks. NeurIPS 2020 - [c53]Saurabh Kumar, Aviral Kumar, Sergey Levine, Chelsea Finn:
One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL. NeurIPS 2020 - [c52]Lisa Lee, Ben Eysenbach, Ruslan Salakhutdinov, Shixiang Shane Gu, Chelsea Finn:
Weakly-Supervised Reinforcement Learning for Controllable Behavior. NeurIPS 2020 - [c51]Karl Pertsch, Oleh Rybkin, Frederik Ebert, Shenghao Zhou, Dinesh Jayaraman, Chelsea Finn, Sergey Levine:
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. NeurIPS 2020 - [c50]Kelvin Xu, Siddharth Verma, Chelsea Finn, Sergey Levine:
Continual Learning of Control Primitives : Skill Discovery via Reset-Games. NeurIPS 2020 - [c49]Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn:
Gradient Surgery for Multi-Task Learning. NeurIPS 2020 - [c48]Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y. Zou, Sergey Levine, Chelsea Finn, Tengyu Ma:
MOPO: Model-based Offline Policy Optimization. NeurIPS 2020 - [i88]Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn:
Gradient Surgery for Multi-Task Learning. CoRR abs/2001.06782 (2020) - [i87]Xingyou Song, Yuxiang Yang, Krzysztof Choromanski, Ken Caluwaerts, Wenbo Gao, Chelsea Finn, Jie Tan:
Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning. CoRR abs/2003.01239 (2020) - [i86]Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn:
Scalable Multi-Task Imitation Learning with Autonomous Improvement. CoRR abs/2003.02636 (2020) - [i85]Akhil Padmanabha, Frederik Ebert, Stephen Tian, Roberto Calandra, Chelsea Finn, Sergey Levine:
OmniTact: A Multi-Directional High Resolution Touch Sensor. CoRR abs/2003.06965 (2020) - [i84]Lisa Lee, Benjamin Eysenbach, Ruslan Salakhutdinov, Shixiang Gu, Chelsea Finn:
Weakly-Supervised Reinforcement Learning for Controllable Behavior. CoRR abs/2004.02860 (2020) - [i83]Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman:
Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation. CoRR abs/2004.10190 (2020) - [i82]Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma:
MOPO: Model-based Offline Policy Optimization. CoRR abs/2005.13239 (2020) - [i81]Russell Mendonca, Xinyang Geng, Chelsea Finn, Sergey Levine:
Meta-Reinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling. CoRR abs/2006.07178 (2020) - [i80]Annie Xie, James Harrison, Chelsea Finn:
Deep Reinforcement Learning amidst Lifelong Non-Stationarity. CoRR abs/2006.10701 (2020) - [i79]Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine:
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. CoRR abs/2006.13205 (2020) - [i78]Marvin Zhang, Henrik Marklund, Abhishek Gupta, Sergey Levine, Chelsea Finn:
Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift. CoRR abs/2007.02931 (2020) - [i77]Allan Zhou, Tom Knowles, Chelsea Finn:
Meta-Learning Symmetries by Reparameterization. CoRR abs/2007.02933 (2020) - [i76]Suraj Nair, Silvio Savarese, Chelsea Finn:
Goal-Aware Prediction: Learning to Model What Matters. CoRR abs/2007.07170 (2020) - [i75]Evan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn:
Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning. CoRR abs/2008.02790 (2020) - [i74]Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn:
Offline Meta-Reinforcement Learning with Advantage Weighting. CoRR abs/2008.06043 (2020) - [i73]Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman:
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings. CoRR abs/2008.06622 (2020) - [i72]Annie S. Chen, HyunJi Nam, Suraj Nair, Chelsea Finn:
Batch Exploration with Examples for Scalable Robotic Reinforcement Learning. CoRR abs/2010.11917 (2020) - [i71]Tony Z. Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine:
MELD: Meta-Reinforcement Learning from Images via Latent State Models. CoRR abs/2010.13957 (2020) - [i70]Saurabh Kumar, Aviral Kumar, Sergey Levine, Chelsea Finn:
One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL. CoRR abs/2010.14484 (2020) - [i69]Krishnan Srinivasan, Benjamin Eysenbach, Sehoon Ha, Jie Tan, Chelsea Finn:
Learning to be Safe: Deep RL with a Safety Critic. CoRR abs/2010.14603 (2020) - [i68]Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn:
Measuring and Harnessing Transference in Multi-Task Learning. CoRR abs/2010.15413 (2020) - [i67]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. CoRR abs/2010.15920 (2020) - [i66]Kelvin Xu, Siddharth Verma, Chelsea Finn, Sergey Levine:
Continual Learning of Control Primitives: Skill Discovery via Reset-Games. CoRR abs/2011.05286 (2020) - [i65]Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn:
Reinforcement Learning with Videos: Combining Offline Observations with Interaction. CoRR abs/2011.06507 (2020) - [i64]Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh:
Learning Latent Representations to Influence Multi-Agent Interaction. CoRR abs/2011.06619 (2020) - [i63]Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, Dumitru Erhan:
Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning. CoRR abs/2012.04603 (2020) - [i62]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:
WILDS: A Benchmark of in-the-Wild Distribution Shifts. CoRR abs/2012.07421 (2020) - [i61]Tianhe Yu, Xinyang Geng, Chelsea Finn, Sergey Levine:
Variable-Shot Adaptation for Online Meta-Learning. CoRR abs/2012.07769 (2020) - [i60]Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn:
Offline Reinforcement Learning from Images with Latent Space Models. CoRR abs/2012.11547 (2020) - [i59]Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine:
Model-Based Visual Planning with Self-Supervised Functional Distances. CoRR abs/2012.15373 (2020)
2010 – 2019
- 2019
- [c47]Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Jie Tan, Chelsea Finn:
NoRML: No-Reward Meta Learning. AAMAS 2019: 323-331 - [c46]Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, Chelsea Finn:
RoboNet: Large-Scale Multi-Robot Learning. CoRL 2019: 885-897 - [c45]Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, Sergey Levine:
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning. CoRL 2019: 1094-1100 - [c44]Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua B. Tenenbaum, Sergey Levine:
Entity Abstraction in Visual Model-Based Reinforcement Learning. CoRL 2019: 1439-1456 - [c43]Kyle Hsu, Sergey Levine, Chelsea Finn:
Unsupervised Learning via Meta-Learning. ICLR (Poster) 2019 - [c42]Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn, Jiajun Wu:
Reasoning About Physical Interactions with Object-Oriented Prediction and Planning. ICLR (Poster) 2019 - [c41]Anusha Nagabandi, Ignasi Clavera, Simin Liu, Ronald S. Fearing, Pieter Abbeel, Sergey Levine, Chelsea Finn:
Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning. ICLR (Poster) 2019 - [c40]Anusha Nagabandi, Chelsea Finn, Sergey Levine:
Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL. ICLR (Poster) 2019 - [c39]Chelsea Finn, Aravind Rajeswaran, Sham M. Kakade, Sergey Levine:
Online Meta-Learning. ICML 2019: 1920-1930 - [c38]Kate Rakelly, Aurick Zhou, Chelsea Finn, Sergey Levine, Deirdre Quillen:
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables. ICML 2019: 5331-5340 - [c37]Kelvin Xu, Ellis Ratner, Anca D. Dragan, Sergey Levine, Chelsea Finn:
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning. ICML 2019: 6952-6962 - [c36]Stephen Tian, Frederik Ebert, Dinesh Jayaraman, Mayur Mudigonda, Chelsea Finn, Roberto Calandra, Sergey Levine:
Manipulation by Feel: Touch-Based Control with Deep Predictive Models. ICRA 2019: 818-824 - [c35]Tianhe Yu, Pieter Abbeel, Sergey Levine, Chelsea Finn:
One-Shot Composition of Vision-Based Skills from Demonstration. IROS 2019: 2643-2650 - [c34]Aravind Rajeswaran, Chelsea Finn, Sham M. Kakade, Sergey Levine:
Meta-Learning with Implicit Gradients. NeurIPS 2019: 113-124 - [c33]Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn:
Language as an Abstraction for Hierarchical Deep Reinforcement Learning. NeurIPS 2019: 9414-9426 - [c32]Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn:
Guided Meta-Policy Search. NeurIPS 2019: 9653-9664 - [c31]Allan Jabri, Kyle Hsu, Abhishek Gupta, Ben Eysenbach, Sergey Levine, Chelsea Finn:
Unsupervised Curricula for Visual Meta-Reinforcement Learning. NeurIPS 2019: 10519-10530 - [c30]Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon:
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables. NeurIPS 2019: 11749-11760 - [c29]Avi Singh, Larry Yang, Chelsea Finn, Sergey Levine:
End-To-End Robotic Reinforcement Learning without Reward Engineering. Robotics: Science and Systems 2019 - [c28]Annie Xie, Frederik Ebert, Sergey Levine, Chelsea Finn:
Improvisation through Physical Understanding: Using Novel Objects As Tools with Visual Foresight. Robotics: Science and Systems 2019 - [c27]Tianhe Yu, Gleb Shevchuk, Dorsa Sadigh, Chelsea Finn:
Unsupervised Visuomotor Control through Distributional Planning Networks. Robotics: Science and Systems 2019 - [i58]Tianhe Yu, Gleb Shevchuk, Dorsa Sadigh, Chelsea Finn:
Unsupervised Visuomotor Control through Distributional Planning Networks. CoRR abs/1902.05542 (2019) - [i57]Chelsea Finn, Aravind Rajeswaran, Sham M. Kakade, Sergey Levine:
Online Meta-Learning. CoRR abs/1902.08438 (2019) - [i56]Lukasz Kaiser, Mohammad Babaeizadeh, Piotr Milos, Blazej Osinski, Roy H. Campbell, Konrad Czechowski, Dumitru Erhan, Chelsea Finn, Piotr Kozakowski, Sergey Levine, Ryan Sepassi, George Tucker, Henryk Michalewski:
Model-Based Reinforcement Learning for Atari. CoRR abs/1903.00374 (2019) - [i55]Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Jie Tan, Chelsea Finn:
NoRML: No-Reward Meta Learning. CoRR abs/1903.01063 (2019) - [i54]Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma:
VideoFlow: A Flow-Based Generative Model for Video. CoRR abs/1903.01434 (2019) - [i53]Stephen Tian, Frederik Ebert, Dinesh Jayaraman, Mayur Mudigonda, Chelsea Finn, Roberto Calandra, Sergey Levine:
Manipulation by Feel: Touch-Based Control with Deep Predictive Models. CoRR abs/1903.04128 (2019) - [i52]Kate Rakelly, Aurick Zhou, Deirdre Quillen, Chelsea Finn, Sergey Levine:
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables. CoRR abs/1903.08254 (2019) - [i51]Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn:
Guided Meta-Policy Search. CoRR abs/1904.00956 (2019) - [i50]Annie Xie, Frederik Ebert, Sergey Levine, Chelsea Finn:
Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight. CoRR abs/1904.05538 (2019) - [i49]Avi Singh, Larry Yang, Kristian Hartikainen, Chelsea Finn, Sergey Levine:
End-to-End Robotic Reinforcement Learning without Reward Engineering. CoRR abs/1904.07854 (2019) - [i48]Allan Zhou, Eric Jang, Daniel Kappler, Alexander Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn:
Watch, Try, Learn: Meta-Learning from Demonstrations and Reward. CoRR abs/1906.03352 (2019) - [i47]Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn:
Language as an Abstraction for Hierarchical Deep Reinforcement Learning. CoRR abs/1906.07343 (2019) - [i46]Mark Woodward, Chelsea Finn, Karol Hausman:
Training an Interactive Helper. CoRR abs/1906.10165 (2019) - [i45]Mark Woodward, Chelsea Finn, Karol Hausman:
Learning to Interactively Learn and Assist. CoRR abs/1906.10187 (2019) - [i44]Aravind Rajeswaran, Chelsea Finn, Sham M. Kakade, Sergey Levine:
Meta-Learning with Implicit Gradients. CoRR abs/1909.04630 (2019) - [i43]Suraj Nair, Chelsea Finn:
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation. CoRR abs/1909.05829 (2019) - [i42]Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon:
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables. CoRR abs/1909.09314 (2019) - [i41]Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, Sergey Levine:
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning. CoRR abs/1910.10897 (2019) - [i40]Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, Chelsea Finn:
RoboNet: Large-Scale Multi-Robot Learning. CoRR abs/1910.11215 (2019) - [i39]Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua B. Tenenbaum, Sergey Levine:
Entity Abstraction in Visual Model-Based Reinforcement Learning. CoRR abs/1910.12827 (2019) - [i38]Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn:
Meta-Learning without Memorization. CoRR abs/1912.03820 (2019) - [i37]Allan Jabri, Kyle Hsu, Ben Eysenbach, Abhishek Gupta, Sergey Levine, Chelsea Finn:
Unsupervised Curricula for Visual Meta-Reinforcement Learning. CoRR abs/1912.04226 (2019) - [i36]Glen Berseth, Daniel Geng, Coline Devin, Chelsea Finn, Dinesh Jayaraman, Sergey Levine:
SMiRL: Surprise Minimizing RL in Dynamic Environments. CoRR abs/1912.05510 (2019) - [i35]James Harrison, Apoorva Sharma, Chelsea Finn, Marco Pavone:
Continuous Meta-Learning without Tasks. CoRR abs/1912.08866 (2019) - [i34]Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine, Chelsea Finn:
Learning Predictive Models From Observation and Interaction. CoRR abs/1912.12773 (2019) - 2018
- [b1]Chelsea Finn:
Learning to Learn with Gradients. University of California, Berkeley, USA, 2018 - [c26]Annie Xie, Avi Singh, Sergey Levine, Chelsea Finn:
Few-Shot Goal Inference for Visuomotor Learning and Planning. CoRL 2018: 40-52 - [c25]Frederik Ebert, Sudeep Dasari, Alex X. Lee, Sergey Levine, Chelsea Finn:
Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning. CoRL 2018: 983-993 - [c24]Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine:
Stochastic Variational Video Prediction. ICLR (Poster) 2018 - [c23]Chelsea Finn, Sergey Levine:
Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm. ICLR (Poster) 2018 - [c22]Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, Thomas L. Griffiths:
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes. ICLR (Poster) 2018 - [c21]Tianhe Yu, Chelsea Finn, Annie Xie, Sudeep Dasari, Tianhao Zhang, Pieter Abbeel, Sergey Levine:
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning. ICLR (Workshop) 2018 - [c20]Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn:
Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control. ICML 2018: 4739-4748 - [c19]Deirdre Quillen, Eric Jang, Ofir Nachum, Chelsea Finn, Julian Ibarz, Sergey Levine:
Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods. ICRA 2018: 6284-6291 - [c18]Chelsea Finn, Kelvin Xu, Sergey Levine:
Probabilistic Model-Agnostic Meta-Learning. NeurIPS 2018: 9537-9548 - [c17]Tianhe Yu, Chelsea Finn, Sudeep Dasari, Annie Xie, Tianhao Zhang, Pieter Abbeel, Sergey Levine:
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning. Robotics: Science and Systems 2018 - [i33]Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, Thomas L. Griffiths:
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes. CoRR abs/1801.08930 (2018) - [i32]Tianhe Yu, Chelsea Finn, Annie Xie, Sudeep Dasari, Tianhao Zhang, Pieter Abbeel, Sergey Levine:
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning. CoRR abs/1802.01557 (2018) - [i31]Deirdre Quillen, Eric Jang, Ofir Nachum, Chelsea Finn, Julian Ibarz, Sergey Levine:
Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods. CoRR abs/1802.10264 (2018) - [i30]Ignasi Clavera, Anusha Nagabandi, Ronald S. Fearing, Pieter Abbeel, Sergey Levine, Chelsea Finn:
Learning to Adapt: Meta-Learning for Model-Based Control. CoRR abs/1803.11347 (2018) - [i29]Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn:
Universal Planning Networks. CoRR abs/1804.00645 (2018) - [i28]Alex X. Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, Sergey Levine:
Stochastic Adversarial Video Prediction. CoRR abs/1804.01523 (2018) - [i27]Kelvin Xu, Ellis Ratner, Anca D. Dragan, Sergey Levine, Chelsea Finn:
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning. CoRR abs/1805.12573 (2018) - [i26]Chelsea Finn, Kelvin Xu, Sergey Levine:
Probabilistic Model-Agnostic Meta-Learning. CoRR abs/1806.02817 (2018) - [i25]Abhishek Gupta, Benjamin Eysenbach, Chelsea Finn, Sergey Levine:
Unsupervised Meta-Learning for Reinforcement Learning. CoRR abs/1806.04640 (2018) - [i24]Annie Xie, Avi Singh, Sergey Levine, Chelsea Finn:
Few-Shot Goal Inference for Visuomotor Learning and Planning. CoRR abs/1810.00482 (2018) - [i23]Suraj Nair, Mohammad Babaeizadeh, Chelsea Finn, Sergey Levine, Vikash Kumar:
Time Reversal as Self-Supervision. CoRR abs/1810.01128 (2018) - [i22]Kyle Hsu, Sergey Levine, Chelsea Finn:
Unsupervised Learning via Meta-Learning. CoRR abs/1810.02334 (2018) - [i21]Frederik Ebert, Sudeep Dasari, Alex X. Lee, Sergey Levine, Chelsea Finn:
Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning. CoRR abs/1810.03043 (2018) - [i20]Tianhe Yu, Pieter Abbeel, Sergey Levine, Chelsea Finn:
One-Shot Hierarchical Imitation Learning of Compound Visuomotor Tasks. CoRR abs/1810.11043 (2018) - [i19]Frederik Ebert, Chelsea Finn, Sudeep Dasari, Annie Xie, Alex X. Lee, Sergey Levine:
Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control. CoRR abs/1812.00568 (2018) - [i18]Anusha Nagabandi, Chelsea Finn, Sergey Levine:
Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL. CoRR abs/1812.07671 (2018) - [i17]Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn, Jiajun Wu:
Reasoning About Physical Interactions with Object-Oriented Prediction and Planning. CoRR abs/1812.10972 (2018) - 2017
- [c16]Frederik Ebert, Chelsea Finn, Alex X. Lee, Sergey Levine:
Self-Supervised Visual Planning with Temporal Skip Connections. CoRL 2017: 344-356 - [c15]Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, Sergey Levine:
One-Shot Visual Imitation Learning via Meta-Learning. CoRL 2017: 357-368 - [c14]Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine:
Generalizing Skills with Semi-Supervised Reinforcement Learning. ICLR (Poster) 2017 - [c13]Chelsea Finn, Pieter Abbeel, Sergey Levine:
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks. ICML 2017: 1126-1135 - [c12]Chelsea Finn, Sergey Levine:
Deep visual foresight for planning robot motion. ICRA 2017: 2786-2793 - [c11]William Montgomery, Anurag Ajay, Chelsea Finn, Pieter Abbeel, Sergey Levine:
Reset-free guided policy search: Efficient deep reinforcement learning with stochastic initial states. ICRA 2017: 3373-3380 - [i16]Mark Woodward, Chelsea Finn:
Active One-shot Learning. CoRR abs/1702.06559 (2017) - [i15]Chelsea Finn, Pieter Abbeel, Sergey Levine:
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks. CoRR abs/1703.03400 (2017) - [i14]Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, Sergey Levine:
One-Shot Visual Imitation Learning via Meta-Learning. CoRR abs/1709.04905 (2017) - [i13]Frederik Ebert, Chelsea Finn, Alex X. Lee, Sergey Levine:
Self-Supervised Visual Planning with Temporal Skip Connections. CoRR abs/1710.05268 (2017) - [i12]Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine:
Stochastic Variational Video Prediction. CoRR abs/1710.11252 (2017) - [i11]Chelsea Finn, Sergey Levine:
Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm. CoRR abs/1710.11622 (2017) - 2016
- [j2]Sergey Levine, Chelsea Finn, Trevor Darrell, Pieter Abbeel:
End-to-End Training of Deep Visuomotor Policies. J. Mach. Learn. Res. 17: 39:1-39:40 (2016) - [c10]Chelsea Finn, Sergey Levine, Pieter Abbeel:
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization. ICML 2016: 49-58 - [c9]Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, Pieter Abbeel:
Deep spatial autoencoders for visuomotor learning. ICRA 2016: 512-519 - [c8]Marvin Zhang, Zoe McCarthy, Chelsea Finn, Sergey Levine, Pieter Abbeel:
Learning deep neural network policies with continuous memory states. ICRA 2016: 520-527 - [c7]Chelsea Finn, Ian J. Goodfellow, Sergey Levine:
Unsupervised Learning for Physical Interaction through Video Prediction. NIPS 2016: 64-72 - [c6]Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Pieter Abbeel, Sergey Levine, Kate Saenko, Trevor Darrell:
Adapting Deep Visuomotor Representations with Weak Pairwise Constraints. WAFR 2016: 688-703 - [i10]Chelsea Finn, Sergey Levine, Pieter Abbeel:
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization. CoRR abs/1603.00448 (2016) - [i9]Chelsea Finn, Ian J. Goodfellow, Sergey Levine:
Unsupervised Learning for Physical Interaction through Video Prediction. CoRR abs/1605.07157 (2016) - [i8]Chelsea Finn, Sergey Levine:
Deep Visual Foresight for Planning Robot Motion. CoRR abs/1610.00696 (2016) - [i7]William Montgomery, Anurag Ajay, Chelsea Finn, Pieter Abbeel, Sergey Levine:
Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial States. CoRR abs/1610.01112 (2016) - [i6]Chelsea Finn, Paul F. Christiano, Pieter Abbeel, Sergey Levine:
A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models. CoRR abs/1611.03852 (2016) - [i5]Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine:
Generalizing Skills with Semi-Supervised Reinforcement Learning. CoRR abs/1612.00429 (2016) - 2015
- [j1]James Duyck, Chelsea Finn, Andy Hutcheon, Pablo Vera, Joaquín Salas, Sai Ravela:
Sloop: A pattern retrieval engine for individual animal identification. Pattern Recognit. 48(4): 1059-1073 (2015) - [c5]Dylan Hadfield-Menell, Alex X. Lee, Chelsea Finn, Eric Tzeng, Sandy H. Huang, Pieter Abbeel:
Beyond lowest-warping cost action selection in trajectory transfer. ICRA 2015: 3231-3238 - [c4]Hsueh-Cheng Wang, Chelsea Finn, Liam Paull, Michael Kaess, Ruth Rosenholtz, Seth J. Teller, John J. Leonard:
Bridging text spotting and SLAM with junction features. IROS 2015: 3701-3708 - [c3]Chelsea Finn, Lisa Anne Hendricks, Trevor Darrell:
Learning Compact Convolutional Neural Networks with Nested Dropout. ICLR (Workshop) 2015 - [i4]Sergey Levine, Chelsea Finn, Trevor Darrell, Pieter Abbeel:
End-to-End Training of Deep Visuomotor Policies. CoRR abs/1504.00702 (2015) - [i3]Marvin Zhang, Sergey Levine, Zoe McCarthy, Chelsea Finn, Pieter Abbeel:
Policy Learning with Continuous Memory States for Partially Observed Robotic Control. CoRR abs/1507.01273 (2015) - [i2]Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, Pieter Abbeel:
Learning Visual Feature Spaces for Robotic Manipulation with Deep Spatial Autoencoders. CoRR abs/1509.06113 (2015) - [i1]Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Xingchao Peng, Sergey Levine, Kate Saenko, Trevor Darrell:
Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments. CoRR abs/1511.07111 (2015) - 2014
- [c2]Chelsea Finn, James Duyck, Andy Hutcheon, Pablo Vera, Joaquín Salas, Sai Ravela:
Relevance Feedback in Biometric Retrieval of Animal Photographs. MCPR 2014: 281-290 - 2013
- [c1]Sai Ravela, James Duyck, Chelsea Finn:
Vision-Based Biometrics for Conservation. MCPR 2013: 10-19
Coauthor Index
Frederik Ebert
aka: Frederik D. Ebert
aka: Frederik D. Ebert
Benjamin Eysenbach
aka: Ben Eysenbach
aka: Ben Eysenbach
Kyle Hatch
aka: Kyle Beltran Hatch
aka: Kyle Beltran Hatch
Alex Irpan
aka: Alexander Irpan
aka: Alexander Irpan
[c185] [c184] [c174] [c171] [c168] [c167] [i234] [i233] [i230] [i225] [i223] [i217] [i216] [i213] [i210] [i208] [i207] [i202] [c161] [c160] [c154] [c148] [c143] [c140] [c135] [c132] [c131] [i194] [i193] [i188] [i186] [i176] [i171] [i169] [i168] [i166] [i163] [i161] [i157] [c129] [c125] [c122] [c121] [c114] [c111] [c105] [c103] [i152] [i151] [i150] [i141] [i134] [i131] [i122] [j5] [c100] [c99] [c98] [c95] [c94] [c92] [c90] [c87] [c81] [c80] [c78] [c76] [c74] [i121] [i120] [i115] [i114] [i112] [i108] [i102] [i99] [i98] [i97] [i92] [i91] [i90] [i89] [c71] [c69] [c68] [c67] [c66] [c65] [c63] [c62] [c59] [c58] [c57] [c56] [c53] [c51] [c50] [c49] [c48] [i88] [i86] [i85] [i83] [i82] [i81] [i79] [i78] [i74] [i73] [i71] [i70] [i66] [i65] [i63] [i62] [i61] [i59] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c32] [c31] [c29] [c28] [i57] [i56] [i54] [i53] [i52] [i51] [i50] [i49] [i48] [i44] [i41] [i40] [i39] [i38] [i37] [i36] [i34] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [i33] [i32] [i31] [i30] [i29] [i28] [i27] [i26] [i25] [i24] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [c16] [c15] [c14] [c13] [c12] [c11] [i15] [i14] [i13] [i12] [i11] [j2] [c10] [c9] [c8] [c7] [c6] [i10] [i9] [i8] [i7] [i6] [i5] [i4] [i3] [i2] [i1]
[c168] [c160] [c154] [c144] [c143] [c135] [i179] [i171] [i169] [i166] [i154] [c127] [c114] [c112] [i151] [i145] [i136] [i122] [c84] [c83] [c80] [c75] [c74] [i120] [i111] [i103] [i102] [c61] [c49] [c48] [i88] [i82] [i68] [i61] [i60] [c45] [c35] [c30] [c27] [i58] [i42] [i41] [c21] [c17] [i32] [i20] [c15] [c14] [i14] [i5]
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of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-06 21:32 CET by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
