Aravind Rajeswaran

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All published works

Action	Title	Year	Authors
+ PDF Chat	Semi-Supervised One-Shot Imitation Learning	2024	Philipp Wu Kourosh Hakhamaneshi Yuqing Du Igor Mordatch Aravind Rajeswaran Pieter Abbeel
+ PDF Chat	MoDem-V2: Visuo-Motor World Models for Real-World Robot Manipulation	2024	Patrick Lancaster Nicklas Hansen Aravind Rajeswaran Vikash Kumar
+ PDF Chat	What Do We Learn from a Large-Scale Study of Pre-Trained Visual Representations in Sim and Real Environments?	2024	Sneha Silwal Karmesh Yadav Tingfan Wu Jay Vakil Arjun Majumdar Sergio Arnaud Claire Chen Vincent-Pierre Berges Dhruv Batra Aravind Rajeswaran
+ PDF Chat	From LLMs to Actions: Latent Codes as Bridges in Hierarchical Robot Control	2024	Yide Shentu Philipp Wu Aravind Rajeswaran Pieter Abbeel
+ PDF Chat	Train Offline, Test Online: A Real Robot Learning Benchmark	2023	Gaoyue Zhou Victoria Dean Mohan Kumar Srirama Aravind Rajeswaran Jyothish Pari Kyle Hatch Aryan Jain Tianhe Yu Pieter Abbeel Lerrel Pinto
+ PDF Chat	Real World Offline Reinforcement Learning with Realistic Data Source	2023	Gaoyue Zhou Liyiming Ke Siddhartha S Srinivasa Abhinav Gupta Aravind Rajeswaran Vikash Kumar
+	Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?	2023	Arjun Majumdar Karmesh Yadav Sergio Arnaud Yecheng Jason Ma Claire Chen Sneha Silwal Aryan Jain Vincent-Pierre Berges Pieter Abbeel Jitendra Malik
+	Masked Trajectory Models for Prediction, Representation, and Control	2023	Philipp Wu Arjun Majumdar Kevin H. Stone Yixin Lin Igor Mordatch Pieter Abbeel Aravind Rajeswaran
+	Train Offline, Test Online: A Real Robot Learning Benchmark	2023	Gaoyue Zhou Victoria Dean Mohan Kumar Srirama Aravind Rajeswaran Jyothish Pari Kyle Hatch Aryan Jain Tianhe Yu Pieter Abbeel Lerrel Pinto
+	MoDem-V2: Visuo-Motor World Models for Real-World Robot Manipulation	2023	Patrick Lancaster Nicklas Hansen Aravind Rajeswaran Vikash Kumar
+	What do we learn from a large-scale study of pre-trained visual representations in sim and real environments?	2023	Sneha Silwal Karmesh Yadav Tingfan Wu Jay Vakil Arjun Majumdar Sergio Arnaud Claire Chen Vincent-Pierre Berges Dhruv Batra Aravind Rajeswaran
+	RoboHive: A Unified Framework for Robot Learning	2023	Vikas Kumar Rutav Shah Gaoyue Zhou Vincent Moens Vittorio Caggiano Jay Vakil Abhishek Gupta Aravind Rajeswaran
+	CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery	2022	Michael Laskin Hao Liu Xue Bin Peng Denis Yarats Aravind Rajeswaran Pieter Abbeel
+	R3M: A Universal Visual Representation for Robot Manipulation	2022	Suraj Nair Aravind Rajeswaran Vikash Kumar Chelsea Finn Abhinav Gupta
+	The Unsurprising Effectiveness of Pre-Trained Vision Models for Control	2022	Simone Parisi Aravind Rajeswaran Senthil Purushwalkam Abhinav Gupta
+	Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation?	2022	Yuchen Cui Scott Niekum Abhinav Gupta Vikas Kumar Aravind Rajeswaran
+	Policy Architectures for Compositional Generalization in Control	2022	Allan Zhou Vikash Kumar Chelsea Finn Aravind Rajeswaran
+	Real World Offline Reinforcement Learning with Realistic Data Source	2022	Gaoyue Zhou Liyiming Ke Siddhartha S Srinivasa Abhinav Gupta Aravind Rajeswaran Vikas Kumar
+	CACTI: A Framework for Scalable Multi-Task Multi-Scene Visual Imitation Learning	2022	Zhao Mandi Homanga Bharadhwaj Vincent Moens Shuran Song Aravind Rajeswaran Vikash Kumar
+	MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations	2022	Nicklas Hansen Yixin Lin Hao Su Xiaolong Wang Vikash Kumar Aravind Rajeswaran
+	On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline	2022	Nicklas Hansen Zhecheng Yuan Yanjie Ze Tongzhou Mu Aravind Rajeswaran Hao Su Huazhe Xu Xiaolong Wang
+	Visual Adversarial Imitation Learning using Variational Models	2021	Rafael Rafailov Tianhe Yu Aravind Rajeswaran Chelsea Finn
+	COMBO: Conservative Offline Model-Based Policy Optimization	2021	Tianhe Yu Aviral Kumar Rafael Rafailov Aravind Rajeswaran Sergey Levine Chelsea Finn
+	Reinforcement Learning with Latent Flow	2021	Wenling Shang Xiaofei Wang Aravind Srinivas Aravind Rajeswaran Yang Gao Pieter Abbeel Michael Laskin
+	Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL	2021	Catherine Cang Aravind Rajeswaran Pieter Abbeel Michael Laskin
+	Decision Transformer: Reinforcement Learning via Sequence Modeling	2021	Lili Chen Kevin Lü Aravind Rajeswaran Kimin Lee Aditya Grover Michael Laskin Pieter Abbeel Aravind Srinivas Igor Mordatch
+	COMBO: Conservative Offline Model-Based Policy Optimization	2021	Tianhe Yu Aviral Kumar Rafael Rafailov Aravind Rajeswaran Sergey Levine Chelsea Finn
+	Reinforcement Learning with Latent Flow	2021	Wenling Shang Xiaofei Wang Aravind Rajeswaran Aravind Srinivas Yang Gao Pieter Abbeel Michael Laskin
+	Visual Adversarial Imitation Learning using Variational Models	2021	Rafael Rafailov Tianhe Yu Aravind Rajeswaran Chelsea Finn
+	Offline Reinforcement Learning from Images with Latent Space Models	2020	Rafael Rafailov Tianhe Yu Aravind Rajeswaran Chelsea Finn
+	Lyceum: An efficient and scalable ecosystem for robot learning	2020	Colin Summers Kendall Lowrey Aravind Rajeswaran Siddhartha S Srinivasa Emanuel Todorov
+	A Game Theoretic Framework for Model Based Reinforcement Learning	2020	Aravind Rajeswaran Igor Mordatch Vikash Kumar
+	MOReL : Model-Based Offline Reinforcement Learning	2020	Rahul Kidambi Aravind Rajeswaran Praneeth Netrapalli Thorsten Joachims
+	Offline Reinforcement Learning from Images with Latent Space Models	2020	Rafael Rafailov Tianhe Yu Aravind Rajeswaran Chelsea Finn
+	Lyceum: An efficient and scalable ecosystem for robot learning	2020	Colin Summers Kendall Lowrey Aravind Rajeswaran Siddhartha S Srinivasa Emanuel Todorov
+ PDF Chat	Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost	2019	Henry Zhu Abhishek Gupta Aravind Rajeswaran Sergey Levine Vikash Kumar
+	Online Meta-Learning	2019	Chelsea Finn Aravind Rajeswaran Sham M. Kakade Sergey Levine
+	Meta-Learning with Implicit Gradients	2019	Aravind Rajeswaran Chelsea Finn Sham M. Kakade Sergey Levine
+	Online Meta-Learning	2019	Chelsea Finn Aravind Rajeswaran Sham M. Kakade Sergey Levine
+	Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control	2018	Kendall Lowrey Aravind Rajeswaran Sham M. Kakade Emanuel Todorov Igor Mordatch
+	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations	2018	Aravind Rajeswaran Vikash Kumar Abhishek Gupta Giulia Vezzani John Schulman Emanuel Todorov Sergey Levine
+ PDF Chat	Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system	2018	Kendall Lowrey Svetoslav Kolev Jeremy Dao Aravind Rajeswaran Emanuel Todorov
+	Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system	2018	Kendall Lowrey Svetoslav Kolev Jeremy Dao Aravind Rajeswaran Emanuel Todorov
+	Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines	2018	Cathy Wu Aravind Rajeswaran Yan Duan Vikash Kumar Alexandre M. Bayen Sham M. Kakade Igor Mordatch Pieter Abbeel
+	Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines	2018	Cathy Wu Aravind Rajeswaran Yan Duan Vikash Kumar Alexandre M. Bayen Sham M. Kakade Igor Mordatch Pieter Abbeel
+	Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost	2018	Henry Zhu Abhishek Gupta Aravind Rajeswaran Sergey Levine Vikash Kumar
+	Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control	2018	Kendall Lowrey Aravind Rajeswaran Sham M. Kakade Emanuel Todorov Igor Mordatch
+	Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system	2018	Kendall Lowrey Svetoslav Kolev Jeremy Dao Aravind Rajeswaran Emanuel Todorov
+	Divide-and-Conquer Reinforcement Learning	2017	Dibya Ghosh Avi Singh Aravind Rajeswaran Vikash Kumar Sergey Levine
+	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations	2017	Aravind Rajeswaran Vikash Kumar Abhishek Gupta John Schulman Emanuel Todorov Sergey Levine
+ PDF Chat	A graph partitioning algorithm for leak detection in water distribution networks	2017	Aravind Rajeswaran Sridharakumar Narasimhan Shankar Narasimhan
+	Towards Generalization and Simplicity in Continuous Control	2017	Aravind Rajeswaran Kendall Lowrey Emanuel Todorov Sham M. Kakade
+	Divide-and-Conquer Reinforcement Learning	2017	Dibya Ghosh Avi Singh Aravind Rajeswaran Vikash Kumar Sergey Levine
+	Towards Generalization and Simplicity in Continuous Control	2017	Aravind Rajeswaran Kendall Lowrey Emanuel Todorov Sham M. Kakade
+	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations	2017	Aravind Rajeswaran Vikas Kumar Abhishek Gupta Giulia Vezzani John Schulman Emanuel Todorov Sergey Levine
+	EPOpt: Learning Robust Neural Network Policies Using Model Ensembles	2016	Aravind Rajeswaran Sarvjeet Ghotra Balaraman Ravindran Sergey Levine
+	EPOpt: Learning Robust Neural Network Policies Using Model Ensembles	2016	Aravind Rajeswaran Sarvjeet Ghotra Balaraman Ravindran Sergey Levine
+	Identifying Topology of Power Distribution Networks Based on Smart Meter Data.	2016	Jayadev P. Satya Nirav Bhatt Ramkrishna Pasumarthy Aravind Rajeswaran
+ PDF Chat	A novel approach for phase identification in smart grids using Graph Theory and Principal Component Analysis	2016	Satya P. Jayadev Aravind Rajeswaran Nirav Bhatt Ramkrishna Pasumarthy
+	A Graph Partitioning Algorithm for Leak Detection in Water Distribution Networks	2016	Aravind Rajeswaran Sridharakumar Narasimhan Shankar Narasimhan
+	Identifying Topology of Power Distribution Networks Based on Smart Meter Data	2016	Jayadev P Satya Nirav Bhatt Ramkrishna Pasumarthy Aravind Rajeswaran
+	EPOpt: Learning Robust Neural Network Policies Using Model Ensembles	2016	Aravind Rajeswaran Sarvjeet Ghotra Balaraman Ravindran Sergey Levine
+	A Graph Partitioning Algorithm for Leak Detection in Water Distribution Networks	2016	Aravind Rajeswaran Sridharakumar Narasimhan Shankar Narasimhan
+	A Novel Approach for Phase Identification in Smart Grids Using Graph Theory and Principal Component Analysis	2015	P Satya Jayadev Aravind Rajeswaran Nirav Bhatt Ramkrishna Pasumarthy
+	A New Method for Reconstructing Network Topology from Flux Measurements.	2015	Aravind Rajeswaran Shankar Narasimhan
+	Network Topology Identification using PCA and its Graph Theoretic Interpretations	2015	Aravind Rajeswaran Shankar Narasimhan
+	A Novel Approach for Phase Identification in Smart Grids Using Graph Theory and Principal Component Analysis	2015	P Satya Jayadev Aravind Rajeswaran Nirav Bhatt Ramkrishna Pasumarthy

Common Coauthors

Coauthor	Papers Together
Sergey Levine	15
Pieter Abbeel	13
Chelsea Finn	13
Emanuel Todorov	12
Sham M. Kakade	9
Kendall Lowrey	9
Igor Mordatch	8
Tianhe Yu	8
Vikash Kumar	7
Rafael Rafailov	6
Ramkrishna Pasumarthy	5
Abhishek Gupta	5
Gaoyue Zhou	5
Vikash Kumar	5
Shankar Narasimhan	5
Siddhartha S Srinivasa	4
Abhinav Gupta	4
Nicklas Hansen	4
Nirav Bhatt	4
Vikash Kumar	4
Vikas Kumar	4
Arjun Majumdar	4
Claire Chen	3
Jeremy Dao	3
Karmesh Yadav	3
Balaraman Ravindran	3
Sridharakumar Narasimhan	3
Vincent-Pierre Berges	3
Oleksandr Maksymets	3
Yixin Lin	3
Aryan Jain	3
Sneha Silwal	3
Sergio Arnaud	3
Jay Vakil	3
Franziska Meier	3
Michael Laskin	3
Philipp Wu	3
Sarvjeet Ghotra	3
Dhruv Batra	3
Aravind Srinivas	3
Liyiming Ke	2
P Satya Jayadev	2
Henry Zhu	2
Alexandre M. Bayen	2
Giulia Vezzani	2
Wenling Shang	2
John Schulman	2
Patrick Lancaster	2
Xiaofei Wang	2
Kyle Hatch	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Trust Region Policy Optimization	2015	John Schulman Sergey Levine Philipp Moritz Michael I. Jordan Pieter Abbeel	11
+	Benchmarking Deep Reinforcement Learning for Continuous Control	2016	Yan Duan Xi Chen Rein Houthooft John Schulman Pieter Abbeel	7
+	Proximal Policy Optimization Algorithms	2017	John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov	7
+	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations	2018	Aravind Rajeswaran Vikash Kumar Abhishek Gupta Giulia Vezzani John Schulman Emanuel Todorov Sergey Levine	6
+	D4RL: Datasets for Deep Data-Driven Reinforcement Learning	2020	Justin Fu Aviral Kumar Ofir Nachum George Tucker Sergey Levine	6
+	Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems	2020	Sergey Levine Aviral Kumar George Tucker Justin Fu	6
+	MOPO: Model-based Offline Policy Optimization	2020	Tianhe Yu Garrett Thomas Lantao Yu Stefano Ermon James Zou Sergey Levine Chelsea Finn Tengyu Ma	5
+	Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction	2019	Aviral Kumar Justin Fu Matthew Soh George Tucker Sergey Levine	5
+	Behavior Regularized Offline Reinforcement Learning	2019	Yifan Wu George Tucker Ofir Nachum	5
+ PDF Chat	Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates	2017	Shixiang Gu Ethan Holly Timothy Lillicrap Sergey Levine	5
+	Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control	2018	Kendall Lowrey Aravind Rajeswaran Sham M. Kakade Emanuel Todorov Igor Mordatch	5
+	Conservative Q-Learning for Offline Reinforcement Learning	2020	Aviral Kumar Aurick Zhou George Tucker Sergey Levine	4
+	Continuous control with deep reinforcement learning	2016	Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel Nicolas Heess Tom Erez Yuval Tassa David Silver Daan Wierstra	4
+	Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards	2017	Matej Vecerík Todd Hester Jonathan Scholz Fumin Wang Olivier Pietquin Bilal Piot Nicolas Heess Thomas Rothörl Thomas Lampe Martin Riedmiller	4
+	Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog	2019	Natasha Jaques Asma Ghandeharioun Judy Hanwen Shen Craig Ferguson Àgata Lapedriza Noah Jones Shixiang Gu Rosalind W. Picard	4
+	Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning	2019	Xue Bin Peng Aviral Kumar Grace Zhang Sergey Levine	4
+	Off-Policy Policy Gradient with State Distribution Correction	2019	Yao Liu Adith Swaminathan Alekh Agarwal Emma Brunskill	4
+ PDF Chat	Learning dexterous in-hand manipulation	2019	OpenAI Marcin Andrychowicz Bowen Baker Maciek Chociej Rafał Józefowicz Bob McGrew Jakub Pachocki Arthur J Petron Matthias Plappert Glenn Powell Alex Ray	4
+	EPOpt: Learning Robust Neural Network Policies Using Model Ensembles	2016	Aravind Rajeswaran Sarvjeet Ghotra Balaraman Ravindran Sergey Levine	4
+	Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor	2018	Tuomas Haarnoja Aurick Zhou Pieter Abbeel Sergey Levine	4
+ PDF Chat	Deconstructing principal component analysis using a data reconciliation perspective	2015	Shankar Narasimhan Nirav Bhatt	4
+	Conservative Q-Learning for Offline Reinforcement Learning	2020	Aviral Kumar Aurick Zhou George Tucker Sergey Levine	3
+	Model-Based Offline Planning	2020	Arthur Argenson Gabriel Dulac-Arnold	3
+ PDF Chat	The Arcade Learning Environment: An Evaluation Platform for General Agents	2013	Marc G. Bellemare Yavar Naddaf Joel Veness Michael Bowling	3
+	MOReL : Model-Based Offline Reinforcement Learning	2020	Rahul Kidambi Aravind Rajeswaran Praneeth Netrapalli Thorsten Joachims	3
+	Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning	2020	Noah Siegel Jost Tobias Springenberg Felix Berkenkamp Abbas Abdolmaleki Michael Neunert Thomas Lampe Roland Hafner Nicolas Heess Martin Riedmiller	3
+	A New Method for Reconstructing Network Topology from Flux Measurements.	2015	Aravind Rajeswaran Shankar Narasimhan	3
+	Provably Good Batch Reinforcement Learning Without Great Exploration	2020	Yao Liu Adith Swaminathan Alekh Agarwal Emma Brunskill	3
+	Principal Component Analysis	2005	Ian T. Jolliffe	3
+ PDF Chat	Sim-to-Real Transfer of Robotic Control with Dynamics Randomization	2018	Xue Bin Peng Marcin Andrychowicz Wojciech Zaremba Pieter Abbeel	3
+	Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels	2020	Ilya Kostrikov Denis Yarats Rob Fergus	3
+	Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization	2020	Tatsuya Matsushima Hiroki Furuta Yutaka Matsuo Ofir Nachum Shixiang Gu	3
+	Decision Transformer: Reinforcement Learning via Sequence Modeling	2021	Lili Chen Kevin Lü Aravind Rajeswaran Kimin Lee Aditya Grover Michael Laskin Pieter Abbeel Aravind Srinivas Igor Mordatch	3
+	Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning	2019	Tianhe Yu Deirdre Quillen Zhanpeng He Ryan Julian Avnish Narayan Hayden Shively Adithya Bellathur Karol Hausman Chelsea Finn Sergey Levine	3
+ PDF Chat	Deep Reinforcement Learning That Matters	2018	Peter Henderson Riashat Islam Philip Bachman Joëlle Pineau Doina Precup David Meger	3
+ PDF Chat	Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost	2019	Henry Zhu Abhishek Gupta Aravind Rajeswaran Sergey Levine Vikash Kumar	3
+	Asynchronous Methods for Deep Reinforcement Learning	2016	Volodymyr Mnih Adrià Puigdomènech Badia Mehdi Mirza Alex Graves Tim Harley Timothy Lillicrap David Silver Koray Kavukcuoglu	3
+	Emergence of Locomotion Behaviours in Rich Environments	2017	Nicolas Heess Dhruva Tb Sriram Srinivasan Jay Lemmon Josh Merel Greg Wayne Yuval Tassa Tom Erez Ziyu Wang S. M. Ali Eslami	3
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	3
+ PDF Chat	Overcoming Exploration in Reinforcement Learning with Demonstrations	2018	Ashvin Nair Bob McGrew Marcin Andrychowicz Wojciech Zaremba Pieter Abbeel	3
+	Finite-Time Bounds for Fitted Value Iteration	2008	Rémi Munos Csaba Szepesvári	3
+ PDF Chat	Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours	2016	Lerrel Pinto Abhinav Gupta	3
+	A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning	2010	Stéphane Ross Geoffrey J. Gordon J. Andrew Bagnell	3
+	Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control	2018	Frederik Ebert Chelsea Finn Sudeep Dasari Annie Xie Alex X. Lee Sergey Levine	3
+	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations	2017	Aravind Rajeswaran Vikash Kumar Abhishek Gupta John Schulman Emanuel Todorov Sergey Levine	3
+ PDF Chat	Path integral guided policy search	2017	Yevgen Chebotar Mrinal Kalakrishnan Ali Abdullah Yahya Adrian Li Stefan Schaal Sergey Levine	3
+	Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models	2018	Kurtland Chua Roberto Calandra Rowan McAllister Sergey Levine	3
+	Dream to Control: Learning Behaviors by Latent Imagination	2019	Danijar Hafner Timothy Lillicrap Jimmy Ba Mohammad Norouzi	3
+	AlgaeDICE: Policy Gradient from Arbitrary Experience	2019	Ofir Nachum Bo Dai Ilya Kostrikov Yinlam Chow Lihong Li Dale Schuurmans	3
+	R3M: A Universal Visual Representation for Robot Manipulation	2022	Suraj Nair Aravind Rajeswaran Vikash Kumar Chelsea Finn Abhinav Gupta	3