Corey Lynch
Impact in
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- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
- Advanced Vision and Imaging
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- Domain Adaptation and Few-Shot Learning
- Anomaly Detection Techniques and Applications
Papers in
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- Multimodal Machine Learning Applications 6
- Human Pose and Action Recognition 5
- Advanced Vision and Imaging 4
- Image Retrieval and Classification Techniques 2
- Advanced Image and Video Retrieval Techniques 2
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- Robot Manipulation and Learning 4
- Co-authors
- Pierre Sermanet (8 shared papers)Sergey Levine (4 shared papers)Jasmine Hsu (3 shared papers)Stefan Schaal (1 shared paper)Eric Jang (1 shared paper)Yevgen Chebotar (1 shared paper)Jonathan Tompson (3 shared papers)Josh Attenberg (2 shared papers)
- Journals
- IEEE Robotics and Automation Letters (1 paper)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)
- Partner nations
- United States
In The Last Decade
Corey Lynch
12 papers receiving 527 citations
Corey Lynch's Hit Papers
Peers
Comparison fields: 5 of 77
- Computer Vision and Pattern Recognition 303
- Artificial Intelligence 315
- Control and Systems Engineering 180
- Human-Computer Interaction 19
- Health Informatics 3
Countries citing papers authored by Corey Lynch
This map shows the geographic impact of Corey Lynch'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 Corey Lynch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Corey Lynch more than expected).
Fields of papers citing papers by Corey Lynch
This network shows the impact of papers produced by Corey Lynch. 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 Corey Lynch. The network helps show where Corey Lynch may publish in the future.
Co-authors
The 21 scholars most cited alongside Corey Lynch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Time-Contrastive Networks: Self-Supervised Learning from Video Hit paper breakdown → | 2018 | 305 |
| 2 | 2017 | 63 | |
| 3 | 2021 | 59 | |
| 4 | Interactive Language: Talking to Robots in Real Time Hit paper breakdown → | 2024 | 46 |
| 5 | 2018 | 27 | |
| 6 | 2016 | 22 | |
| 7 | 2022 | 9 | |
| 8 | 2020 | 7 | |
| 9 | Time-Contrastive Networks: Self-Supervised Learning from Multi-View Observation | 2017 | 6 |
| 10 | 2023 | 4 | |
| 11 | 2023 | 3 | |
| 12 | 2014 | 1 |
About Corey Lynch
Corey Lynch is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Artificial Intelligence, Social Psychology and Atomic and Molecular Physics, and Optics, having authored 12 papers that have together received 552 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (6 papers), Human Pose and Action Recognition (5 papers), Robot Manipulation and Learning (4 papers), Advanced Vision and Imaging (4 papers), Reinforcement Learning in Robotics (3 papers), Image Retrieval and Classification Techniques (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (303 citations), Artificial Intelligence (315 citations), Control and Systems Engineering (180 citations), Human-Computer Interaction (19 citations) and Health Informatics (3 citations). Corey Lynch has collaborated with scholars based in United States. Frequent co-authors include Pierre Sermanet, Sergey Levine, Jasmine Hsu, Stefan Schaal, Eric Jang, Yevgen Chebotar, Jonathan Tompson, Josh Attenberg, Debidatta Dwibedi and Tianli Ding. Their work appears in journals such as IEEE Robotics and Automation Letters and 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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.