Eric Jang
Impact in
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- Domain Adaptation and Few-Shot Learning
- Adversarial Robustness in Machine Learning
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- Robot Manipulation and Learning
Papers in
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- Reinforcement Learning in Robotics 6
- Topic Modeling 1
- Anomaly Detection Techniques and Applications 1
- Machine Learning and Data Classification 1
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- Robot Manipulation and Learning 2
- Co-authors
- Sergey Levine (4 shared papers)Corey Lynch (1 shared paper)Jasmine Hsu (1 shared paper)Stefan Schaal (1 shared paper)Yevgen Chebotar (1 shared paper)Pierre Sermanet (1 shared paper)Chelsea Finn (2 shared papers)Ofir Nachum (1 shared paper)
- Journals
- Frontiers in Neural Circuits (1 paper)Proceedings - IEEE International Conference on Robotics and Automation/Proceedings (5 papers)IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (1 paper)MPG.PuRe (Max Planck Society) (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Eric Jang
9 papers receiving 774 citations
Eric Jang's Hit Papers
Peers
Comparison fields: 5 of 55
- Artificial Intelligence 431
- Control and Systems Engineering 262
- Computer Vision and Pattern Recognition 174
- Industrial and Manufacturing Engineering 13
- Signal Processing 10
Countries citing papers authored by Eric Jang
This map shows the geographic impact of Eric Jang'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 Eric Jang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Jang more than expected).
Fields of papers citing papers by Eric Jang
This network shows the impact of papers produced by Eric Jang. 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 Eric Jang. The network helps show where Eric Jang may publish in the future.
Co-authors
The 23 scholars most cited alongside Eric Jang, 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 | 397 |
| 2 | 2018 | 146 | |
| 3 | 2018 | 81 | |
| 4 | 2021 | 59 | |
| 5 | Categorical Reparametrization with Gumble-Softmax | 2017 | 53 |
| 6 | Generative Ensembles for Robust Anomaly Detection | 2018 | 30 |
| 7 | 2020 | 21 | |
| 8 | 2016 | 5 | |
| 9 | 2023 | 3 |
About Eric Jang
Eric Jang is a scholar working on Artificial Intelligence, Control and Systems Engineering, Cognitive Neuroscience, Computer Vision and Pattern Recognition and Nuclear Energy and Engineering, having authored 9 papers that have together received 795 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (6 papers), Robot Manipulation and Learning (2 papers), Advanced Neural Network Applications (1 paper), Topic Modeling (1 paper), Anomaly Detection Techniques and Applications (1 paper), Neural dynamics and brain function (1 paper), Machine Learning and Data Classification (1 paper) and Visual perception and processing mechanisms (1 paper). The work is most often cited by research in Artificial Intelligence (431 citations), Control and Systems Engineering (262 citations), Computer Vision and Pattern Recognition (174 citations), Industrial and Manufacturing Engineering (13 citations) and Signal Processing (10 citations). Eric Jang has collaborated with scholars based in United States and Germany. Frequent co-authors include Sergey Levine, Corey Lynch, Jasmine Hsu, Stefan Schaal, Yevgen Chebotar, Pierre Sermanet, Chelsea Finn, Ofir Nachum, Julian Ibarz and Alexander Toshev. Their work appears in journals such as Frontiers in Neural Circuits, Proceedings - IEEE International Conference on Robotics and Automation/Proceedings, IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings and MPG.PuRe (Max Planck Society).
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.