Suraj Nair

According to our database, Suraj Nair authored at least 23 papers between 2018 and 2024.

Collaborative distances:

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

2024

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.

Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna, Sudeep Dasari, Siddharth Karamcheti, Soroush Nasiriany, Mohan Kumar Srirama, Lawrence Yunliang Chen, Kirsty Ellis, Peter David Fagan, Joey Hejna, Masha Itkina, Marion Lepert, Yecheng Jason Ma, Patrick Tree Miller, Jimmy Wu, Suneel Belkhale, Shivin Dass, Huy Ha, Arhan Jain, Abraham Lee, Youngwoon Lee, Marius Memmel, Sungjae Park, Ilija Radosavovic, Kaiyuan Wang, Albert Zhan, Kevin Black, Cheng Chi, Kyle Beltran Hatch, Shan Lin, Jingpei Lu, Jean Mercat, Abdul Rehman, Pannag R. Sanketi, Archit Sharma, Cody Simpson, Quan Vuong, Homer Rich Walke, Blake Wulfe, Ted Xiao, Jonathan Heewon Yang, Arefeh Yavary, Tony Z. Zhao, Christopher Agia, Rohan Baijal, Mateo Guaman Castro, Daphne Chen, Qiuyu Chen, Trinity Chung, Jaimyn Drake, Ethan Paul Foster, et al.

CoRR, 2024

Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models.

Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang, Thomas Kollar, Dorsa Sadigh

CoRR, 2024

2023

Language-Driven Representation Learning for Robotics.

Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang

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

Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets.

Maximilian Du, Suraj Nair, Dorsa Sadigh, Chelsea Finn

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

2022

Play it by Ear: Learning Skills amidst Occlusion through Audio-Visual Imitation Learning.

Maximilian Du, Olivia Y. Lee, Suraj Nair, Chelsea Finn

Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

R3M: A Universal Visual Representation for Robot Manipulation.

Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, Abhinav Gupta

Proceedings of the Conference on Robot Learning, 2022

2021

Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones.

Brijen Thananjeyan, Ashwin Balakrishna, Suraj Nair, Michael Luo, Krishnan Srinivasan, Minho Hwang, Joseph E. Gonzalez, Julian Ibarz, Chelsea Finn, Ken Goldberg

IEEE Robotics Autom. Lett., 2021

Batch Exploration With Examples for Scalable Robotic Reinforcement Learning.

Annie S. Chen, HyunJi Nam, Suraj Nair, Chelsea Finn

IEEE Robotics Autom. Lett., 2021

MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance.

Michael Luo, Ashwin Balakrishna, Brijen Thananjeyan, Suraj Nair, Julian Ibarz, Jie Tan, Chelsea Finn, Ion Stoica, Ken Goldberg

CoRR, 2021

FitVid: Overfitting in Pixel-Level Video Prediction.

Mohammad Babaeizadeh, Mohammad Taghi Saffar, Suraj Nair, Sergey Levine, Chelsea Finn, Dumitru Erhan

CoRR, 2021

Learning Generalizable Robotic Reward Functions from "In-The-Wild" Human Videos.

Annie S. Chen, Suraj Nair, Chelsea Finn

Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Model-Based Visual Planning with Self-Supervised Functional Distances.

Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine

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

Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction.

Bohan Wu, Suraj Nair, Roberto Martín-Martín, Li Fei-Fei, Chelsea Finn

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks.

Bohan Wu, Suraj Nair, Li Fei-Fei, Chelsea Finn

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

Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation.

Suraj Nair, Eric Mitchell, Kevin Chen, Brian Ichter, Silvio Savarese, Chelsea Finn

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

2020

TRASS: Time Reversal as Self-Supervision.

Suraj Nair, Mohammad Babaeizadeh, Chelsea Finn, Sergey Levine, Vikash Kumar

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Goal-Aware Prediction: Learning to Model What Matters.

Suraj Nair, Silvio Savarese, Chelsea Finn

Proceedings of the 37th International Conference on Machine Learning, 2020

Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation.

Suraj Nair, Chelsea Finn

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

2019

Causal Induction from Visual Observations for Goal Directed Tasks.

Suraj Nair, Yuke Zhu, Silvio Savarese, Li Fei-Fei

CoRR, 2019

Neural Task Graphs: Generalizing to Unseen Tasks From a Single Video Demonstration.

De-An Huang, Suraj Nair, Danfei Xu, Yuke Zhu, Animesh Garg, Li Fei-Fei, Silvio Savarese, Juan Carlos Niebles

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

RoboNet: Large-Scale Multi-Robot Learning.

Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, Chelsea Finn

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

2018

Time Reversal as Self-Supervision.

Suraj Nair, Mohammad Babaeizadeh, Chelsea Finn, Sergey Levine, Vikash Kumar

CoRR, 2018

Neural Task Programming: Learning to Generalize Across Hierarchical Tasks.

Danfei Xu, Suraj Nair, Yuke Zhu, Julian Gao, Animesh Garg, Li Fei-Fei, Silvio Savarese

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