Abhishek Gupta

According to our database, Abhishek Gupta authored at least 64 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning.

Jianlan Luo, Zheyuan Hu, Charles Xu, You Liang Tan, Jacob Berg, Archit Sharma, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine

CoRR, 2024

2023

Modeling Boundedly Rational Agents with Latent Inference Budgets.

Athul Paul Jacob, Abhishek Gupta, Jacob Andreas

CoRR, 2023

Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning.

Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du

CoRR, 2023

RoboHive: A Unified Framework for Robot Learning.

Vikash Kumar, Rutav M. Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Jay Vakil, Abhishek Gupta, Aravind Rajeswaran

CoRR, 2023

Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback.

Marcel Torne, Max Balsells, Zihan Wang, Samedh Desai, Tao Chen, Pulkit Agrawal, Abhishek Gupta

CoRR, 2023

Self-Supervised Reinforcement Learning that Transfers using Random Features.

Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta

CoRR, 2023

GenAug: Retargeting behaviors to unseen situations via Generative Augmentation.

Zoey Qiuyu Chen, Shosuke C. Kiami, Abhishek Gupta, Vikash Kumar

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability.

Chuning Zhu, Max Simchowitz, Siri Gadipudi, Abhishek Gupta

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

RoboHive: A Unified Framework for Robot Learning.

Vikash Kumar, Rutav M. Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Abhishek Gupta, Aravind Rajeswaran

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance.

Kelvin Xu, Zheyuan Hu, Ria Doshi, Aaron Rovinsky, Vikash Kumar, Abhishek Gupta, Sergey Levine

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

TactoFind: A Tactile Only System for Object Retrieval.

Sameer Pai, Tao Chen, Megha Tippur, Edward H. Adelson, Abhishek Gupta, Pulkit Agrawal

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning.

Abhishek Gupta, Corey Lynch, Brandon Kinman, Garrett Peake, Sergey Levine, Karol Hausman

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Guiding Pretraining in Reinforcement Learning with Large Language Models.

Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, Jacob Andreas

Proceedings of the International Conference on Machine Learning, 2023

Learning to Extrapolate: A Transductive Approach.

Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal

Proceedings of the Eleventh International Conference on Learning Representations, 2023

REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation.

Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine

Proceedings of the Conference on Robot Learning, 2023

Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective.

Max Simchowitz, Abhishek Gupta, Kaiqing Zhang

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Distributionally Adaptive Meta Reinforcement Learning.

Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity.

Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham M. Kakade, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Autonomous Reinforcement Learning: Formalism and Benchmarking.

Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

ReLMM: Practical RL for Learning Mobile Manipulation Skills Using Only Onboard Sensors.

Charles Sun, Jedrzej Orbik, Coline Devin, Brian H. Yang, Abhishek Gupta, Glen Berseth, Sergey Levine

CoRR, 2021

Persistent Reinforcement Learning via Subgoal Curricula.

Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn

CoRR, 2021

Adaptive Risk Minimization: Learning to Adapt to Domain Shift.

Marvin Zhang, Henrik Marklund, Nikita Dhawan, Abhishek Gupta, Sergey Levine, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Teachable Reinforcement Learning via Advice Distillation.

Olivia Watkins, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Jacob Andreas

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Autonomous Reinforcement Learning via Subgoal Curricula.

Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Which Mutual-Information Representation Learning Objectives are Sufficient for Control?

Kate Rakelly, Abhishek Gupta, Carlos Florensa, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention.

Abhishek Gupta, Justin Yu, Tony Z. Zhao, Vikash Kumar, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, Sergey Levine

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning.

Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr H. Pong, Aurick Zhou, Justin Yu, Sergey Levine

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning to Reach Goals via Iterated Supervised Learning.

Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine

Proceedings of the 9th International Conference on Learning Representations, 2021

Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation.

Charles Sun, Jedrzej Orbik, Coline Manon Devin, Brian H. Yang, Abhishek Gupta, Glen Berseth, Sergey Levine

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

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

Marvin Zhang, Henrik Marklund, Abhishek Gupta, Sergey Levine, Chelsea Finn

CoRR, 2020

Ecological Reinforcement Learning.

John D. Co-Reyes, Suvansh Sanjeev, Glen Berseth, Abhishek Gupta, Sergey Levine

CoRR, 2020

Accelerating Online Reinforcement Learning with Offline Datasets.

Ashvin Nair, Murtaza Dalal, Abhishek Gupta, Sergey Levine

CoRR, 2020

Gradient Surgery for Multi-Task Learning.

Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction.

Aviral Kumar, Abhishek Gupta, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The Ingredients of Real World Robotic Reinforcement Learning.

Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Learning To Reach Goals Without Reinforcement Learning.

Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine

CoRR, 2019

Learning latent state representation for speeding up exploration.

Giulia Vezzani, Abhishek Gupta, Lorenzo Natale, Pieter Abbeel

CoRR, 2019

Guided Meta-Policy Search.

Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Unsupervised Curricula for Visual Meta-Reinforcement Learning.

Allan Jabri, Kyle Hsu, Abhishek Gupta, Ben Eysenbach, Sergey Levine, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost.

Henry Zhu, Abhishek Gupta, Aravind Rajeswaran, Sergey Levine, Vikash Kumar

Proceedings of the International Conference on Robotics and Automation, 2019

Domain Randomization for Active Pose Estimation.

Xinyi Ren, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Abhishek Gupta, Aviv Tamar, Pieter Abbeel

Proceedings of the International Conference on Robotics and Automation, 2019

Learning Actionable Representations with Goal Conditioned Policies.

Dibya Ghosh, Abhishek Gupta, Sergey Levine

Proceedings of the 7th International Conference on Learning Representations, 2019

Diversity is All You Need: Learning Skills without a Reward Function.

Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine

Proceedings of the 7th International Conference on Learning Representations, 2019

Guiding Policies with Language via Meta-Learning.

John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, Jacob Andreas, John DeNero, Pieter Abbeel, Sergey Levine

Proceedings of the 7th International Conference on Learning Representations, 2019

Automatically Composing Representation Transformations as a Means for Generalization.

Michael Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths

Proceedings of the 7th International Conference on Learning Representations, 2019

ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots.

Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning.

Abhishek Gupta, Vikash Kumar, Corey Lynch, Sergey Levine, Karol Hausman

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018

Soft Actor-Critic Algorithms and Applications.

Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, Sergey Levine

CoRR, 2018

Guiding Policies with Language via Meta-Learning.

John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, John DeNero, Pieter Abbeel, Sergey Levine

CoRR, 2018

Unsupervised Meta-Learning for Reinforcement Learning.

Abhishek Gupta, Benjamin Eysenbach, Chelsea Finn, Sergey Levine

CoRR, 2018

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations.

Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, Giulia Vezzani, John Schulman, Emanuel Todorov, Sergey Levine

Proceedings of the Robotics: Science and Systems XIV, 2018

Meta-Reinforcement Learning of Structured Exploration Strategies.

Abhishek Gupta, Russell Mendonca, Yuxuan Liu, Pieter Abbeel, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation.

Yuxuan Liu, Abhishek Gupta, Pieter Abbeel, Sergey Levine

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings.

John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations.

Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, John Schulman, Emanuel Todorov, Sergey Levine

CoRR, 2017

Learning modular neural network policies for multi-task and multi-robot transfer.

Coline Devin, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Sergey Levine

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning.

Abhishek Gupta, Coline Devin, Yuxuan Liu, Pieter Abbeel, Sergey Levine

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Learning Dexterous Manipulation Policies from Experience and Imitation.

Vikash Kumar, Abhishek Gupta, Emanuel Todorov, Sergey Levine

CoRR, 2016

Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstration.

Abhishek Gupta, Clemens Eppner, Sergey Levine, Pieter Abbeel

CoRR, 2016

Learning dexterous manipulation for a soft robotic hand from human demonstrations.

Abhishek Gupta, Clemens Eppner, Sergey Levine, Pieter Abbeel

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Guided search for task and motion plans using learned heuristics.

Rohan Chitnis, Dylan Hadfield-Menell, Abhishek Gupta, Siddharth Srivastava, Edward Groshev, Christopher Lin, Pieter Abbeel

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

2015

Learning from multiple demonstrations using trajectory-aware non-rigid registration with applications to deformable object manipulation.

Alex X. Lee, Abhishek Gupta, Henry Lu, Sergey Levine, Pieter Abbeel

Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Learning force-based manipulation of deformable objects from multiple demonstrations.

Alex X. Lee, Henry Lu, Abhishek Gupta, Sergey Levine, Pieter Abbeel

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Tractability of Planning with Loops.

Siddharth Srivastava, Shlomo Zilberstein, Abhishek Gupta, Pieter Abbeel, Stuart Russell

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015