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ORCIDAbhishek Gupta 0004
Person information
- affiliation: University of Washington, Department of Computer Science, Seattle, WA, USA
- affiliation (PhD): University of California at Berkeley, Department of Electrical Engineering and Computer Sciences, CA, USA
Other persons with the same name
- Abhishek Gupta — disambiguation page
- Abhishek Gupta 0001
![[0000-0002-6080-855X]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-6080-855X")
— Nanyang Technological University, Singapore (and 1 more) - Abhishek Gupta 0002 — Ohio State University, Columbus, OH, USA (and 1 more)
- Abhishek Gupta 0003 — University of California Davis, CA, USA
- Abhishek Gupta 0005 — Shri Mata Vaishno Devi University, Katra, India (and 3 more)
- Abhishek Gupta 0006 — Indian Institute of Technology Bombay, Department of Mechanical Engineering, Mumbai, India
- Abhishek Gupta 0007 — Toronto Metropolitan University, Canada
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2020 – today
- 2024
[c60]Athul Paul Jacob, Abhishek Gupta, Jacob Andreas:
Modeling Boundedly Rational Agents with Latent Inference Budgets. ICLR 2024- [c59]Liyiming Ke, Yunchu Zhang, Abhay Deshpande, Siddhartha S. Srinivasa, Abhishek Gupta:
CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning. ICLR 2024 - [c58]Marius Memmel, Andrew Wagenmaker, Chuning Zhu, Dieter Fox, Abhishek Gupta:
ASID: Active Exploration for System Identification in Robotic Manipulation. ICLR 2024 - [c57]Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du:
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning. ICLR 2024 - [c56]Meenal Parakh, Alisha Fong, Anthony Simeonov, Tao Chen, Abhishek Gupta, Pulkit Agrawal:
Lifelong Robot Learning with Human Assisted Language Planners. ICRA 2024: 523-529 - [c55]Daniel Yang, Davin Tjia, Jacob Berg, Dima Damen, Pulkit Agrawal, Abhishek Gupta:
Rank2Reward: Learning Shaped Reward Functions from Passive Video. ICRA 2024: 2806-2813 - [c54]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 - [c53]Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs:
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy. ICRA 2024: 6973-6980 - [c52]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 - [i67]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) - [i66]Marcel Torne, Anthony Simeonov, Zechu Li, April Chan, Tao Chen, Abhishek Gupta, Pulkit Agrawal:
Reconciling Reality through Simulation: A Real-to-Sim-to-Real Approach for Robust Manipulation. CoRR abs/2403.03949 (2024) - [i65]Chuning Zhu, Xinqi Wang, Tyler Han, Simon S. Du, Abhishek Gupta:
Transferable Reinforcement Learning via Generalized Occupancy Models. CoRR abs/2403.06328 (2024) - [i64]Marius Memmel, Andrew Wagenmaker, Chuning Zhu, Patrick Yin, Dieter Fox, Abhishek Gupta:
ASID: Active Exploration for System Identification in Robotic Manipulation. CoRR abs/2404.12308 (2024) - [i63]Daniel Yang, Davin Tjia, Jacob Berg, Dima Damen, Pulkit Agrawal, Abhishek Gupta:
Rank2Reward: Learning Shaped Reward Functions from Passive Video. CoRR abs/2404.14735 (2024) - [i62]Zoey Qiuyu Chen, Aaron Walsman, Marius Memmel, Kaichun Mo, Alex Fang, Karthikeya Vemuri, Alan Wu, Dieter Fox, Abhishek Gupta:
URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images. CoRR abs/2405.11656 (2024) - [i61]Abhay Deshpande, Liyiming Ke, Quinn Pfeifer, Abhishek Gupta, Siddhartha S. Srinivasa:
Data Efficient Behavior Cloning for Fine Manipulation via Continuity-based Corrective Labels. CoRR abs/2405.19307 (2024) - [i60]Zoey Qiuyu Chen, Zhao Mandi, Homanga Bharadhwaj, Mohit Sharma, Shuran Song, Abhishek Gupta, Vikash Kumar:
Semantically Controllable Augmentations for Generalizable Robot Learning. CoRR abs/2409.00951 (2024) - 2023
- [c51]Max Simchowitz, Abhishek Gupta, Kaiqing Zhang:
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. COLT 2023: 3356-3468 - [c50]Max Balsells, Marcel Torne Villasevil, Zihan Wang, Samedh Desai, Pulkit Agrawal, Abhishek Gupta:
Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback. CoRL 2023: 774-799 - [c49]Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine:
REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation. CoRL 2023: 1930-1949 - [c48]Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal:
Learning to Extrapolate: A Transductive Approach. ICLR 2023 - [c47]Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, Jacob Andreas:
Guiding Pretraining in Reinforcement Learning with Large Language Models. ICML 2023: 8657-8677 - [c46]Abhishek Gupta, Corey Lynch, Brandon Kinman, Garrett Peake, Sergey Levine, Karol Hausman:
Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning. ICRA 2023: 5020-5026 - [c45]Kelvin Xu, Zheyuan Hu, Ria Doshi, Aaron Rovinsky, Vikash Kumar, Abhishek Gupta, Sergey Levine:
Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance. ICRA 2023: 5938-5945 - [c44]Sameer Pai, Tao Chen, Megha Tippur, Edward H. Adelson, Abhishek Gupta, Pulkit Agrawal:
TactoFind: A Tactile Only System for Object Retrieval. ICRA 2023: 8025-8032 - [c43]Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta:
Self-Supervised Reinforcement Learning that Transfers using Random Features. NeurIPS 2023 - [c42]Zhang-Wei Hong, Aviral Kumar, Sathwik Karnik, Abhishek Bhandwaldar, Akash Srivastava, Joni Pajarinen, Romain Laroche, Abhishek Gupta, Pulkit Agrawal:
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets. NeurIPS 2023 - [c41]Vikash Kumar, Rutav M. Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Abhishek Gupta, Aravind Rajeswaran:
RoboHive: A Unified Framework for Robot Learning. NeurIPS 2023 - [c40]Marcel Torne Villasevil, Max Balsells, Zihan Wang, Samedh Desai, Tao Chen, Pulkit Agrawal, Abhishek Gupta:
Breadcrumbs to the Goal: Supervised Goal Selection from Human-in-the-Loop Feedback. NeurIPS 2023 - [c39]Chuning Zhu, Max Simchowitz, Siri Gadipudi, Abhishek Gupta:
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability. NeurIPS 2023 - [c38]Zoey Qiuyu Chen, Shosuke C. Kiami, Abhishek Gupta, Vikash Kumar:
GenAug: Retargeting behaviors to unseen situations via Generative Augmentation. Robotics: Science and Systems 2023 - [c37]Yunchu Zhang, Liyiming Ke, Abhay Deshpande, Abhishek Gupta, Siddhartha S. Srinivasa:
Cherry-Picking with Reinforcement Learning. Robotics: Science and Systems 2023 - [i59]Zoey Qiuyu Chen, Sho Kiami, Abhishek Gupta, Vikash Kumar:
GenAug: Retargeting behaviors to unseen situations via Generative Augmentation. CoRR abs/2302.06671 (2023) - [i58]Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, Jacob Andreas:
Guiding Pretraining in Reinforcement Learning with Large Language Models. CoRR abs/2302.06692 (2023) - [i57]Yunchu Zhang, Liyiming Ke, Abhay Deshpande, Abhishek Gupta, Siddhartha S. Srinivasa:
Cherry-Picking with Reinforcement Learning. CoRR abs/2303.05508 (2023) - [i56]Sameer Pai, Tao Chen, Megha Tippur, Edward H. Adelson, Abhishek Gupta, Pulkit Agrawal:
TactoFind: A Tactile Only System for Object Retrieval. CoRR abs/2303.13482 (2023) - [i55]Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal:
Learning to Extrapolate: A Transductive Approach. CoRR abs/2304.14329 (2023) - [i54]Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta:
Self-Supervised Reinforcement Learning that Transfers using Random Features. CoRR abs/2305.17250 (2023) - [i53]Max Simchowitz, Abhishek Gupta, Kaiqing Zhang:
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. CoRR abs/2307.06457 (2023) - [i52]Marcel Torne, Max Balsells, Zihan Wang, Samedh Desai, Tao Chen, Pulkit Agrawal, Abhishek Gupta:
Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback. CoRR abs/2307.11049 (2023) - [i51]Chuning Zhu, Max Simchowitz, Siri Gadipudi, Abhishek Gupta:
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability. CoRR abs/2309.00082 (2023) - [i50]Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine:
REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation. CoRR abs/2309.03322 (2023) - [i49]Meenal Parakh, Alisha Fong, Anthony Simeonov, Abhishek Gupta, Tao Chen, Pulkit Agrawal:
Human-Assisted Continual Robot Learning with Foundation Models. CoRR abs/2309.14321 (2023) - [i48]Zhang-Wei Hong, Aviral Kumar, Sathwik Karnik, Abhishek Bhandwaldar, Akash Srivastava, Joni Pajarinen, Romain Laroche, Abhishek Gupta, Pulkit Agrawal:
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets. CoRR abs/2310.04413 (2023) - [i47]Vikash Kumar, Rutav M. Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Jay Vakil, Abhishek Gupta, Aravind Rajeswaran:
RoboHive: A Unified Framework for Robot Learning. CoRR abs/2310.06828 (2023) - [i46]Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs:
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy. CoRR abs/2310.08581 (2023) - [i45]Liyiming Ke, Yunchu Zhang, Abhay Deshpande, Siddhartha S. Srinivasa, Abhishek Gupta:
CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning. CoRR abs/2310.12972 (2023) - [i44]Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du:
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning. CoRR abs/2310.19308 (2023) - [i43]Max Balsells, Marcel Torne, Zihan Wang, Samedh Desai, Pulkit Agrawal, Abhishek Gupta:
Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback. CoRR abs/2310.20608 (2023) - [i42]Athul Paul Jacob, Abhishek Gupta, Jacob Andreas:
Modeling Boundedly Rational Agents with Latent Inference Budgets. CoRR abs/2312.04030 (2023) - 2022
- [c36]Zoey Qiuyu Chen, Karl Van Wyk, Yu-Wei Chao, Wei Yang, Arsalan Mousavian, Abhishek Gupta, Dieter Fox:
Learning Robust Real-World Dexterous Grasping Policies via Implicit Shape Augmentation. CoRL 2022: 1222-1232 - [c35]Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn:
Autonomous Reinforcement Learning: Formalism and Benchmarking. ICLR 2022 - [c34]Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham M. Kakade, Sergey Levine:
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity. NeurIPS 2022 - [c33]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. NeurIPS 2022 - [i41]Olivia Watkins, Trevor Darrell, Pieter Abbeel, Jacob Andreas, Abhishek Gupta:
Teachable Reinforcement Learning via Advice Distillation. CoRR abs/2203.11197 (2022) - [i40]Abhishek Gupta, Corey Lynch, Brandon Kinman, Garrett Peake, Sergey Levine, Karol Hausman:
Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning. CoRR abs/2203.15755 (2022) - [i39]Zoey Qiuyu Chen, Karl Van Wyk, Yu-Wei Chao, Wei Yang, Arsalan Mousavian, Abhishek Gupta, Dieter Fox:
DexTransfer: Real World Multi-fingered Dexterous Grasping with Minimal Human Demonstrations. CoRR abs/2209.14284 (2022) - [i38]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. CoRR abs/2210.03104 (2022) - [i37]Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham M. Kakade, Sergey Levine:
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity. CoRR abs/2210.09579 (2022) - [i36]Zoey Qiuyu Chen, Karl Van Wyk, Yu-Wei Chao, Wei Yang, Arsalan Mousavian, Abhishek Gupta, Dieter Fox:
Learning Robust Real-World Dexterous Grasping Policies via Implicit Shape Augmentation. CoRR abs/2210.13638 (2022) - [i35]Kelvin Xu, Zheyuan Hu, Ria Doshi, Aaron Rovinsky, Vikash Kumar, Abhishek Gupta, Sergey Levine:
Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance. CoRR abs/2212.09902 (2022) - 2021
- [b1]Abhishek Gupta:
How to Train Your Robot: Techniques for Enabling Robotic Learning in the Real World. University of California, Berkeley, USA, 2021 - [c32]Charles Sun, Jedrzej Orbik, Coline Manon Devin, Brian H. Yang, Abhishek Gupta, Glen Berseth, Sergey Levine:
Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation. CoRL 2021: 308-319 - [c31]Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine:
Learning to Reach Goals via Iterated Supervised Learning. ICLR 2021 - [c30]Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr H. Pong, Aurick Zhou, Justin Yu, Sergey Levine:
MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning. ICML 2021: 6346-6356 - [c29]Abhishek Gupta, Justin Yu, Tony Z. Zhao, Vikash Kumar, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, Sergey Levine:
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention. ICRA 2021: 6664-6671 - [c28]Olivia Watkins, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Jacob Andreas:
Teachable Reinforcement Learning via Advice Distillation. NeurIPS 2021: 6920-6933 - [c27]Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn:
Autonomous Reinforcement Learning via Subgoal Curricula. NeurIPS 2021: 18474-18486 - [c26]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 - [c25]Kate Rakelly, Abhishek Gupta, Carlos Florensa, Sergey Levine:
Which Mutual-Information Representation Learning Objectives are Sufficient for Control? NeurIPS 2021: 26345-26357 - [i34]Abhishek Gupta, Justin Yu, Tony Z. Zhao, Vikash Kumar, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, Sergey Levine:
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention. CoRR abs/2104.11203 (2021) - [i33]Kate Rakelly, Abhishek Gupta, Carlos Florensa, Sergey Levine:
Which Mutual-Information Representation Learning Objectives are Sufficient for Control? CoRR abs/2106.07278 (2021) - [i32]Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr Pong, Aurick Zhou, Justin Yu, Sergey Levine:
MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning. CoRR abs/2107.07184 (2021) - [i31]Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn:
Persistent Reinforcement Learning via Subgoal Curricula. CoRR abs/2107.12931 (2021) - [i30]Charles Sun, Jedrzej Orbik, Coline Devin, Brian H. Yang, Abhishek Gupta, Glen Berseth, Sergey Levine:
ReLMM: Practical RL for Learning Mobile Manipulation Skills Using Only Onboard Sensors. CoRR abs/2107.13545 (2021) - [i29]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
- [c24]Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine:
The Ingredients of Real World Robotic Reinforcement Learning. ICLR 2020 - [c23]Aviral Kumar, Abhishek Gupta, Sergey Levine:
DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction. NeurIPS 2020 - [c22]Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn:
Gradient Surgery for Multi-Task Learning. NeurIPS 2020 - [i28]Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn:
Gradient Surgery for Multi-Task Learning. CoRR abs/2001.06782 (2020) - [i27]Aviral Kumar, Abhishek Gupta, Sergey Levine:
DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction. CoRR abs/2003.07305 (2020) - [i26]Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine:
The Ingredients of Real-World Robotic Reinforcement Learning. CoRR abs/2004.12570 (2020) - [i25]Ashvin Nair, Murtaza Dalal, Abhishek Gupta, Sergey Levine:
Accelerating Online Reinforcement Learning with Offline Datasets. CoRR abs/2006.09359 (2020) - [i24]John D. Co-Reyes, Suvansh Sanjeev, Glen Berseth, Abhishek Gupta, Sergey Levine:
Ecological Reinforcement Learning. CoRR abs/2006.12478 (2020) - [i23]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)
2010 – 2019
- 2019
- [c21]Abhishek Gupta, Vikash Kumar, Corey Lynch, Sergey Levine, Karol Hausman:
Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning. CoRL 2019: 1025-1037 - [c20]Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar:
ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots. CoRL 2019: 1300-1313 - [c19]Michael Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths:
Automatically Composing Representation Transformations as a Means for Generalization. ICLR (Poster) 2019 - [c18]John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, Jacob Andreas, John DeNero, Pieter Abbeel, Sergey Levine:
Guiding Policies with Language via Meta-Learning. ICLR (Poster) 2019 - [c17]Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine:
Diversity is All You Need: Learning Skills without a Reward Function. ICLR (Poster) 2019 - [c16]Dibya Ghosh, Abhishek Gupta, Sergey Levine:
Learning Actionable Representations with Goal Conditioned Policies. ICLR (Poster) 2019 - [c15]Henry Zhu, Abhishek Gupta, Aravind Rajeswaran, Sergey Levine, Vikash Kumar:
Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost. ICRA 2019: 3651-3657 - [c14]Xinyi Ren, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Abhishek Gupta, Aviv Tamar, Pieter Abbeel:
Domain Randomization for Active Pose Estimation. ICRA 2019: 7228-7234 - [c13]Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn:
Guided Meta-Policy Search. NeurIPS 2019: 9653-9664 - [c12]Allan Jabri, Kyle Hsu, Abhishek Gupta, Ben Eysenbach, Sergey Levine, Chelsea Finn:
Unsupervised Curricula for Visual Meta-Reinforcement Learning. NeurIPS 2019: 10519-10530 - [i22]Xinyi Ren, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Abhishek Gupta, Aviv Tamar, Pieter Abbeel:
Domain Randomization for Active Pose Estimation. CoRR abs/1903.03953 (2019) - [i21]Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn:
Guided Meta-Policy Search. CoRR abs/1904.00956 (2019) - [i20]Giulia Vezzani, Abhishek Gupta, Lorenzo Natale, Pieter Abbeel:
Learning latent state representation for speeding up exploration. CoRR abs/1905.12621 (2019) - [i19]Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar:
ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots. CoRR abs/1909.11639 (2019) - [i18]Abhishek Gupta, Vikash Kumar, Corey Lynch, Sergey Levine, Karol Hausman:
Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning. CoRR abs/1910.11956 (2019) - [i17]Allan Jabri, Kyle Hsu, Ben Eysenbach, Abhishek Gupta, Sergey Levine, Chelsea Finn:
Unsupervised Curricula for Visual Meta-Reinforcement Learning. CoRR abs/1912.04226 (2019) - [i16]Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine:
Learning To Reach Goals Without Reinforcement Learning. CoRR abs/1912.06088 (2019) - 2018
- [c11]John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine:
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings. ICML 2018: 1008-1017 - [c10]Yuxuan Liu, Abhishek Gupta, Pieter Abbeel, Sergey Levine:
Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation. ICRA 2018: 1118-1125 - [c9]Abhishek Gupta, Russell Mendonca, Yuxuan Liu, Pieter Abbeel, Sergey Levine:
Meta-Reinforcement Learning of Structured Exploration Strategies. NeurIPS 2018: 5307-5316 - [c8]Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, Giulia Vezzani, John Schulman, Emanuel Todorov, Sergey Levine:
Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations. Robotics: Science and Systems 2018 - [i15]Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine:
Diversity is All You Need: Learning Skills without a Reward Function. CoRR abs/1802.06070 (2018) - [i14]Abhishek Gupta, Russell Mendonca, Yuxuan Liu, Pieter Abbeel, Sergey Levine:
Meta-Reinforcement Learning of Structured Exploration Strategies. CoRR abs/1802.07245 (2018) - [i13]John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine:
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings. CoRR abs/1806.02813 (2018) - [i12]Abhishek Gupta, Benjamin Eysenbach, Chelsea Finn, Sergey Levine:
Unsupervised Meta-Learning for Reinforcement Learning. CoRR abs/1806.04640 (2018) - [i11]Michael Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths:
Automatically Composing Representation Transformations as a Means for Generalization. CoRR abs/1807.04640 (2018) - [i10]Henry Zhu, Abhishek Gupta, Aravind Rajeswaran, Sergey Levine, Vikash Kumar:
Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost. CoRR abs/1810.06045 (2018) - [i9]