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ORCIDAbhishek Gupta 0004
Person information
- affiliation: 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.dagstuhl.de/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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Conference and Workshop Papers
- 2023
[c45]Max Simchowitz, Abhishek Gupta, Kaiqing Zhang:
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. COLT 2023: 3356-3468- [c44]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 - [c43]Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal:
Learning to Extrapolate: A Transductive Approach. ICLR 2023 - [c42]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 - [c41]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 - [c40]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 - [c39]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 - [c38]Vikash Kumar, Rutav M. Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Abhishek Gupta, Aravind Rajeswaran:
RoboHive: A Unified Framework for Robot Learning. NeurIPS 2023 - [c37]Chuning Zhu, Max Simchowitz, Siri Gadipudi, Abhishek Gupta:
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability. NeurIPS 2023 - [c36]Zoey Qiuyu Chen, Shosuke C. Kiami, Abhishek Gupta, Vikash Kumar:
GenAug: Retargeting behaviors to unseen situations via Generative Augmentation. Robotics: Science and Systems 2023 - 2022
- [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 - 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 - 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 - 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 - 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 - 2017
- [c7]Abhishek Gupta, Coline Devin, Yuxuan Liu, Pieter Abbeel, Sergey Levine:
Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning. ICLR (Poster) 2017 - [c6]Coline Devin, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Sergey Levine:
Learning modular neural network policies for multi-task and multi-robot transfer. ICRA 2017: 2169-2176 - 2016
- [c5]Rohan Chitnis, Dylan Hadfield-Menell, Abhishek Gupta, Siddharth Srivastava, Edward Groshev, Christopher Lin, Pieter Abbeel:
Guided search for task and motion plans using learned heuristics. ICRA 2016: 447-454 - [c4]Abhishek Gupta, Clemens Eppner, Sergey Levine, Pieter Abbeel:
Learning dexterous manipulation for a soft robotic hand from human demonstrations. IROS 2016: 3786-3793 - 2015
- [c3]Siddharth Srivastava, Shlomo Zilberstein, Abhishek Gupta, Pieter Abbeel, Stuart Russell:
Tractability of Planning with Loops. AAAI 2015: 3393-3401 - [c2]Alex X. Lee, Henry Lu, Abhishek Gupta, Sergey Levine, Pieter Abbeel:
Learning force-based manipulation of deformable objects from multiple demonstrations. ICRA 2015: 177-184 - [c1]Alex X. Lee, Abhishek Gupta, Henry Lu, Sergey Levine, Pieter Abbeel:
Learning from multiple demonstrations using trajectory-aware non-rigid registration with applications to deformable object manipulation. IROS 2015: 5265-5272
Informal and Other Publications
- 2024
- [i52]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) - 2023
- [i51]Zoey Qiuyu Chen, Sho Kiami, Abhishek Gupta, Vikash Kumar:
GenAug: Retargeting behaviors to unseen situations via Generative Augmentation. CoRR abs/2302.06671 (2023) - [i50]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) - [i49]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) - [i48]Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal:
Learning to Extrapolate: A Transductive Approach. CoRR abs/2304.14329 (2023) - [i47]Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta:
Self-Supervised Reinforcement Learning that Transfers using Random Features. CoRR abs/2305.17250 (2023) - [i46]Max Simchowitz, Abhishek Gupta, Kaiqing Zhang:
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. CoRR abs/2307.06457 (2023) - [i45]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) - [i44]Chuning Zhu, Max Simchowitz, Siri Gadipudi, Abhishek Gupta:
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability. CoRR abs/2309.00082 (2023) - [i43]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) - [i42]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) - [i41]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) - [i40]Athul Paul Jacob, Abhishek Gupta, Jacob Andreas:
Modeling Boundedly Rational Agents with Latent Inference Budgets. CoRR abs/2312.04030 (2023) - 2022
- [i39]Olivia Watkins, Trevor Darrell, Pieter Abbeel, Jacob Andreas, Abhishek Gupta:
Teachable Reinforcement Learning via Advice Distillation. CoRR abs/2203.11197 (2022) - [i38]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) - [i37]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. CoRR abs/2210.03104 (2022) - [i36]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) - [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
- [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
- [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) - 2019
- [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
- [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]Dibya Ghosh, Abhishek Gupta, Sergey Levine:
Learning Actionable Representations with Goal-Conditioned Policies. CoRR abs/1811.07819 (2018) - [i8]John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, John DeNero, Pieter Abbeel, Sergey Levine:
Guiding Policies with Language via Meta-Learning. CoRR abs/1811.07882 (2018) - [i7]Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, Sergey Levine:
Soft Actor-Critic Algorithms and Applications. CoRR abs/1812.05905 (2018) - 2017
- [i6]Abhishek Gupta, Coline Devin, Yuxuan Liu, Pieter Abbeel, Sergey Levine:
Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning. CoRR abs/1703.02949 (2017) - [i5]Yuxuan Liu, Abhishek Gupta, Pieter Abbeel, Sergey Levine:
Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation. CoRR abs/1707.03374 (2017) - [i4]Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, John Schulman, Emanuel Todorov, Sergey Levine:
Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations. CoRR abs/1709.10087 (2017) - 2016
- [i3]Abhishek Gupta, Clemens Eppner, Sergey Levine, Pieter Abbeel:
Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstration. CoRR abs/1603.06348 (2016) - [i2]Coline Devin, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Sergey Levine:
Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer. CoRR abs/1609.07088 (2016) - [i1]Vikash Kumar, Abhishek Gupta, Emanuel Todorov, Sergey Levine:
Learning Dexterous Manipulation Policies from Experience and Imitation. CoRR abs/1611.05095 (2016)
Coauthor Index
[c44] [c41] [c40] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c4] [c2] [c1] [i52] [i43] [i38] [i37] [i36] [i35] [i34] [i33] [i32] [i31] [i30] [i29] [i28] [i27] [i26] [i25] [i24] [i23] [i21] [i19] [i18] [i17] [i16] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [i4] [i3] [i2] [i1]
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