Norman Mu
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Co-authors
- Dan HendrycksJustin GilmerSteven BasartSaurav KadavathFengqiu WangSamyak ParajuliDawn SongTyler Zhu
- Topics
- Natural Language Processing Techniques (2 papers)Advanced Vision and Imaging (2 papers)Image and Signal Denoising Methods (1 paper)
- Journals
- ACM Transactions on Asian and Low-Resource Language Information Processing2021 IEEE/CVF International Conference on Computer Vision (ICCV)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
- Partner nations
- United StatesGermany
In The Last Decade
Norman Mu
6 papers receiving 548 citations
Hit Papers
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 407
- Computer Vision and Pattern Recognition 361
- Radiology, Nuclear Medicine and Imaging 48
- Electrical and Electronic Engineering 21
- Control and Systems Engineering 16
Countries citing papers authored by Norman Mu
This map shows the geographic impact of Norman Mu'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 Norman Mu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Norman Mu more than expected).
Fields of papers citing papers by Norman Mu
This network shows the impact of papers produced by Norman Mu. 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 Norman Mu. The network helps show where Norman Mu may publish in the future.
Co-authorship network of co-authors of Norman Mu
This figure shows the co-authorship network connecting the top 25 collaborators of Norman Mu. A scholar is included among the top collaborators of Norman Mu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Norman Mu. Norman Mu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalizationbreakdown → | 503 |
| 5 | AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty | 61 |
| 6 | 1 |
About Norman Mu
Norman Mu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering, having authored 6 papers that have together received 570 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (2 papers), Advanced Vision and Imaging (2 papers) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (361 citations), Artificial Intelligence (407 citations) and Health Informatics (3 citations). Norman Mu has collaborated with scholars based in United States and Germany. Frequent co-authors include Dan Hendrycks, Justin Gilmer, Steven Basart, Saurav Kadavath, Fengqiu Wang, Samyak Parajuli, Dawn Song, Tyler Zhu, Jacob Steinhardt and Barret Zoph. Their work appears in journals such as ACM Transactions on Asian and Low-Resource Language Information Processing, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
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.