Casey Chu
Impact in
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- Probabilistic and Robust Engineering Design
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- Generative Adversarial Networks and Image Synthesis
Papers in
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- Model Reduction and Neural Networks 2
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- Adversarial Robustness in Machine Learning 2
- Reinforcement Learning in Robotics 1
- Co-authors
- Kenji Fukumizu (1 shared paper)Kentaro Minami (1 shared paper)José Blanchet (1 shared paper)Peter W. Glynn (1 shared paper)
- Journals
- arXiv (Cornell University) (2 papers)Scholarship - Claremont (Claremont Colleges) (1 paper)
- Partner nations
- United StatesJapan
In The Last Decade
Casey Chu
3 papers receiving 10 citations
Peers
Comparison fields: 5 of 13
- Statistics, Probability and Uncertainty 2
- Computer Vision and Pattern Recognition 5
- Statistical and Nonlinear Physics 3
- Modeling and Simulation 1
- Artificial Intelligence 6
Countries citing papers authored by Casey Chu
This map shows the geographic impact of Casey Chu'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 Casey Chu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Casey Chu more than expected).
Fields of papers citing papers by Casey Chu
This network shows the impact of papers produced by Casey Chu. 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 Casey Chu. The network helps show where Casey Chu may publish in the future.
Co-authors
The 4 scholars most cited alongside Casey Chu, 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 | 2020 | 5 | |
| 2 | 2019 | 3 | |
| 3 | The Geometry of Data: Distance on Data Manifolds | 2016 | 2 |
About Casey Chu
Casey Chu is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Computer Vision and Pattern Recognition, Infectious Diseases and Organic Chemistry, having authored 3 papers that have together received 10 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (2 papers), Adversarial Robustness in Machine Learning (2 papers), Reinforcement Learning in Robotics (1 paper) and Generative Adversarial Networks and Image Synthesis (1 paper). The work is most often cited by research in Statistics, Probability and Uncertainty (2 citations), Computer Vision and Pattern Recognition (5 citations), Statistical and Nonlinear Physics (3 citations), Modeling and Simulation (1 citation) and Artificial Intelligence (6 citations). Casey Chu has collaborated with scholars based in United States and Japan. Frequent co-authors include Kenji Fukumizu, Kentaro Minami, José Blanchet and Peter W. Glynn. Their work appears in journals such as arXiv (Cornell University) and Scholarship - Claremont (Claremont Colleges).
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.