Sergey Levine

63.4k citations
233 papers · 13.5k · 10 hit papers · h-index 54

Impact in

Papers in

Sergey Levine

227 papers receiving 12.9k citations

Sergey Levine's Hit Papers

Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware 2023 · 228 citations
2280+3+7Years since publication50010001.5k

Peers

Sergey Levine
Comparison fields: 5 of 155
  • Control and Systems Engineering 5.8k
  • Computer Vision and Pattern Recognition 4.8k
  • Artificial Intelligence 6.6k
  • Human-Computer Interaction 465
  • Automotive Engineering 866
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Citations per field
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Citations per year

Countries citing papers authored by Sergey Levine

Since Specialization
Citations

This map shows the geographic impact of Sergey Levine's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sergey Levine with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergey Levine more than expected).

Fields of papers citing papers by Sergey Levine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sergey Levine. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sergey Levine. The network helps show where Sergey Levine may publish in the future.

Co-authors

The 25 scholars most cited alongside Sergey Levine, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sergey Levine Line = papers co-authored together Sergey Levine links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 233 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Trust Region Policy Optimization
Hit paper breakdown →
20151633
2
Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates
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2017935
3
End-to-end training of deep visuomotor policies
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2016771
4
Recurrent Network Models for Human Dynamics
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2015592
5
DeepMimic
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2018484
6
How to train your robot with deep reinforcement learning: lessons we have learned
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2021354
7
Time-Contrastive Networks: Self-Supervised Learning from Video
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2018348
8
Deep visual foresight for planning robot motion
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2017337
9 2017295
10 2018247
11
AMP
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2021232
12
Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
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2023228
13
Guided Policy Search
2013214
14 2017194
15
Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics
2014188
16 2015179
17 2017178
18 2016163
19
Nonlinear Inverse Reinforcement Learning with Gaussian Processes
2011155
20
Learning to poke by poking: experiential learning of intuitive physics
2016138

About Sergey Levine

Sergey Levine is a scholar working on Artificial Intelligence, Control and Systems Engineering, Computer Vision and Pattern Recognition, Biomedical Engineering and Cognitive Neuroscience, having authored 233 papers that have together received 13.5k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (105 papers), Robot Manipulation and Learning (58 papers), Human Pose and Action Recognition (33 papers), Adversarial Robustness in Machine Learning (28 papers), Domain Adaptation and Few-Shot Learning (26 papers), Multimodal Machine Learning Applications (20 papers), Human Motion and Animation (19 papers) and Robotic Path Planning Algorithms (13 papers). The work is most often cited by research in Control and Systems Engineering (5.8k citations), Computer Vision and Pattern Recognition (4.8k citations), Artificial Intelligence (6.6k citations), Human-Computer Interaction (465 citations) and Automotive Engineering (866 citations). Sergey Levine has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Pieter Abbeel, Chelsea Finn, Vladlen Koltun, Shixiang Gu, Michael I. Jordan, John Schulman, Philipp Moritz, Jitendra Malik, Timothy Lillicrap and Xue Bin Peng. Their work appears in journals such as ACM Transactions on Graphics, IEEE Robotics and Automation Letters, The International Journal of Robotics Research, Journal of Machine Learning Research and Journal of NeuroEngineering and Rehabilitation.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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