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Rajeswaran, Aravind
43  Ergebnisse:
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1

Train Offline, Test Online: A Real Robot Learning Benchmark:

, In: 2023 IEEE International Conference on Robotics and Automation (ICRA),
Zhou, Gaoyue ; Dean, Victoria ; Srirama, Mohan Kumar... - p. 9197-9203 , 2023
Link: https://doi.org/10.1109/..
 
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2

Real World Offline Reinforcement Learning with Realistic Da..:

, In: 2023 IEEE International Conference on Robotics and Automation (ICRA),
Zhou, Gaoyue ; Ke, Liyiming ; Srinivasa, Siddhartha... - p. 7176-7183 , 2023
Link: https://doi.org/10.1109/..
 
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3

A graph partitioning algorithm for leak detection in water ..:

Rajeswaran, Aravind ; Narasimhan, Sridharakumar ; Narasimhan, Shankar
Computers & Chemical Engineering.  108 (2018)  - p. 11-23 , 2018
Link: https://doi.org/10.1016/..
 
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4

Masked Trajectory Models for Prediction, Representation, an..:

Wu, Philipp ; Majumdar, Arjun ; Stone, Kevin...
http://arxiv.org/abs/2305.02968.  , 2023
Link: http://arxiv.org/abs/230..
 
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5

What do we learn from a large-scale study of pre-trained vi..:

Silwal, Sneha ; Yadav, Karmesh ; Wu, Tingfan...
http://arxiv.org/abs/2310.02219.  , 2023
Link: http://arxiv.org/abs/231..
 
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6

Where are we in the search for an Artificial Visual Cortex ..:

Majumdar, Arjun ; Yadav, Karmesh ; Arnaud, Sergio...
http://arxiv.org/abs/2303.18240.  , 2023
Link: http://arxiv.org/abs/230..
 
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7

MoDem-V2: Visuo-Motor World Models for Real-World Robot Man..:

Lancaster, Patrick ; Hansen, Nicklas ; Rajeswaran, Aravind.
http://arxiv.org/abs/2309.14236.  , 2023
Link: http://arxiv.org/abs/230..
 
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8

RoboHive: A Unified Framework for Robot Learning:

Kumar, Vikash ; Shah, Rutav ; Zhou, Gaoyue...
http://arxiv.org/abs/2310.06828.  , 2023
Link: http://arxiv.org/abs/231..
 
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9

Train Offline, Test Online: A Real Robot Learning Benchmark:

Zhou, Gaoyue ; Dean, Victoria ; Srirama, Mohan Kumar...
http://arxiv.org/abs/2306.00942.  , 2023
Link: http://arxiv.org/abs/230..
 
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10

CACTI: A Framework for Scalable Multi-Task Multi-Scene Visu..:

Mandi, Zhao ; Bharadhwaj, Homanga ; Moens, Vincent...
http://arxiv.org/abs/2212.05711.  , 2022
Link: http://arxiv.org/abs/221..
 
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11

CIC: Contrastive Intrinsic Control for Unsupervised Skill D..:

Laskin, Michael ; Liu, Hao ; Peng, Xue Bin...
http://arxiv.org/abs/2202.00161.  , 2022
Link: http://arxiv.org/abs/220..
 
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12

The Unsurprising Effectiveness of Pre-Trained Vision Models..:

Parisi, Simone ; Rajeswaran, Aravind ; Purushwalkam, Senthil.
http://arxiv.org/abs/2203.03580.  , 2022
Link: http://arxiv.org/abs/220..
 
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13

Can Foundation Models Perform Zero-Shot Task Specification ..:

Cui, Yuchen ; Niekum, Scott ; Gupta, Abhinav..
http://arxiv.org/abs/2204.11134.  , 2022
Link: http://arxiv.org/abs/220..
 
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14

On Pre-Training for Visuo-Motor Control: Revisiting a Learn..:

Hansen, Nicklas ; Yuan, Zhecheng ; Ze, Yanjie...
http://arxiv.org/abs/2212.05749.  , 2022
Link: http://arxiv.org/abs/221..
 
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15

MoDem: Accelerating Visual Model-Based Reinforcement Learni..:

Hansen, Nicklas ; Lin, Yixin ; Su, Hao...
http://arxiv.org/abs/2212.05698.  , 2022
Link: http://arxiv.org/abs/221..
 
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