Suraj Nair

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Chelsea FinnStanford University, Physical IntelligenceAdresse e-mail validée de cs.stanford.edu
Sergey LevineUC Berkeley, Physical IntelligenceAdresse e-mail validée de eecs.berkeley.edu
Ashwin BalakrishnaGoogle DeepMindAdresse e-mail validée de google.com
Silvio SavareseAssociate Professor of Computer Science at Stanford UniversityAdresse e-mail validée de stanford.edu
Li Fei-FeiProfessor of Computer Science, Stanford UniversityAdresse e-mail validée de cs.stanford.edu
Dorsa SadighStanford UniversityAdresse e-mail validée de cs.stanford.edu
Yuke ZhuThe University of Texas at Austin, NVIDIA ResearchAdresse e-mail validée de cs.utexas.edu
Siddharth KaramchetiPhD Student - Stanford UniversityAdresse e-mail validée de cs.stanford.edu
Percy LiangAssociate Professor of Computer Science, Stanford UniversityAdresse e-mail validée de cs.stanford.edu
Annie S. ChenStanford UniversityAdresse e-mail validée de stanford.edu
Animesh GargGeorgia Institute of Technology, University of Toronto, NvidiaAdresse e-mail validée de gatech.edu
Danfei XuAssistant Professor of Computer Science at Georgia TechAdresse e-mail validée de gatech.edu
Frederik EbertUC BerkeleyAdresse e-mail validée de berkeley.edu
Stephen TianStanford UniversityAdresse e-mail validée de stanford.edu
Sudeep DasariCarnegie Mellon UniversityAdresse e-mail validée de cs.cmu.edu
Brijen ThananjeyanSenior Research Scientist, Ambi RoboticsAdresse e-mail validée de ambirobotics.com
Aravind RajeswaranMeta AI, UC BerkeleyAdresse e-mail validée de cs.washington.edu
Abhinav GuptaProfessor, Robotics Institute, Carnegie Mellon UniversityAdresse e-mail validée de cs.cmu.edu
Mohammad BabaeizadehGoogle BrainAdresse e-mail validée de google.com
De-An HuangStanford UniversityAdresse e-mail validée de cs.stanford.edu

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Suraj Nair

Physical Intelligence

Adresse e-mail validée de physicalintelligence.company - Page d'accueil

Machine Learning Robotics Computer Vision


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021	4610	2021
R3m: A universal visual representation for robot manipulation S Nair, A Rajeswaran, V Kumar, C Finn, A Gupta arXiv preprint arXiv:2203.12601, 2022	514	2022
RoboNet: Large-scale multi-robot learning S Dasari, F Ebert, S Tian, S Nair, B Bucher, K Schmeckpeper, S Singh, ... Conference on Robot Learning (CoRL), 2019	309	2019
Recovery rl: Safe reinforcement learning with learned recovery zones B Thananjeyan, A Balakrishna, S Nair, M Luo, K Srinivasan, M Hwang, ... IEEE Robotics and Automation Letters 6 (3), 4915-4922, 2021	259	2021
Neural task programming: Learning to generalize across hierarchical tasks D Xu, S Nair, Y Zhu, J Gao, A Garg, L Fei-Fei, S Savarese 2018 IEEE international conference on robotics and automation (ICRA), 3795-3802, 2018	246	2018
OpenVLA: An Open-Source Vision-Language-Action Model MJ Kim, K Pertsch, S Karamcheti, T Xiao, A Balakrishna, S Nair, ... arXiv preprint arXiv:2406.09246, 2024	166	2024
Neural task graphs: Generalizing to unseen tasks from a single video demonstration DA Huang, S Nair, D Xu, Y Zhu, A Garg, L Fei-Fei, S Savarese, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019	165	2019
Learning language-conditioned robot behavior from offline data and crowd-sourced annotation S Nair, E Mitchell, K Chen, B Ichter, S Savarese, C Finn Conference on Robot Learning, 1303-1315, 2022	159	2022
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation S Nair, C Finn 2020 International Conference on Learning Representations (ICLR), 2019	154	2019
Reliable real‐time seismic signal/noise discrimination with machine learning MA Meier, ZE Ross, A Ramachandran, A Balakrishna, S Nair, P Kundzicz, ... Journal of Geophysical Research: Solid Earth 124 (1), 788-800, 2019	139	2019
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration⁰ A O’Neill, A Rehman, A Maddukuri, A Gupta, A Padalkar, A Lee, A Pooley, ... 2024 IEEE International Conference on Robotics and Automation (ICRA), 6892-6903, 2024	132	2024
Greedy hierarchical variational autoencoders for large-scale video prediction B Wu, S Nair, R Martin-Martin, L Fei-Fei, C Finn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	123	2021
Language-driven representation learning for robotics S Karamcheti, S Nair, AS Chen, T Kollar, C Finn, D Sadigh, P Liang arXiv preprint arXiv:2302.12766, 2023	122	2023
Learning generalizable robotic reward functions from" in-the-wild" human videos AS Chen, S Nair, C Finn arXiv preprint arXiv:2103.16817, 2021	118	2021
Droid: A large-scale in-the-wild robot manipulation dataset A Khazatsky, K Pertsch, S Nair, A Balakrishna, S Dasari, S Karamcheti, ... arXiv preprint arXiv:2403.12945, 2024	100	2024
Fitvid: Overfitting in pixel-level video prediction M Babaeizadeh, MT Saffar, S Nair, S Levine, C Finn, D Erhan arXiv preprint arXiv:2106.13195, 2021	86	2021
Goal-aware prediction: Learning to model what matters S Nair, S Savarese, C Finn International Conference on Machine Learning, 7207-7219, 2020	75	2020
Model-Based Visual Planning with Self-Supervised Functional Distances S Tian, S Nair, F Ebert, S Dasari, B Eysenbach, C Finn, S Levine 2021 International Conference on Learning Representations (ICLR), 2020	66	2020
Causal induction from visual observations for goal directed tasks S Nair, Y Zhu, S Savarese, L Fei-Fei arXiv preprint arXiv:1910.01751, 2019	66	2019
Prismatic vlms: Investigating the design space of visually-conditioned language models S Karamcheti, S Nair, A Balakrishna, P Liang, T Kollar, D Sadigh arXiv preprint arXiv:2402.07865, 2024	64	2024

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