William Fedus
Impact in
- Biophysics top 1%
- Cell Image Analysis Techniques
- Advanced Fluorescence Microscopy Techniques
- Media Technology top 5%
- Image Processing Techniques and Applications
Papers in
-
- Natural Language Processing Techniques 3
- Domain Adaptation and Few-Shot Learning 2
- Artificial Intelligence in Games 2
- Adversarial Robustness in Machine Learning 1
-
- Advanced Neural Network Applications 2
- Medical Image Segmentation Techniques 1
- Co-authors
- Andrew M. Dai (2 shared papers)Ian Goodfellow (2 shared papers)Yoshua Bengio (2 shared papers)D. Michael Ando (1 shared paper)Piyush Goyal (1 shared paper)Steven Finkbeiner (1 shared paper)Andre Esteva (1 shared paper)Kevan Shah (1 shared paper)
- Journals
- Cell (1 paper)Neural Information Processing Systems (1 paper)Apollo (University of Cambridge) (1 paper)International Conference on Learning Representations (2 papers)arXiv (Cornell University) (4 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
William Fedus
11 papers receiving 792 citations
William Fedus's Hit Papers
Peers
Comparison fields: 5 of 113
- Biophysics 270
- Media Technology 108
- Artificial Intelligence 391
- Computer Vision and Pattern Recognition 200
- Structural Biology 8
Countries citing papers authored by William Fedus
This map shows the geographic impact of William Fedus'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 William Fedus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William Fedus more than expected).
Fields of papers citing papers by William Fedus
This network shows the impact of papers produced by William Fedus. 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 William Fedus. The network helps show where William Fedus may publish in the future.
Co-authors
The 25 scholars most cited alongside William Fedus, 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 | In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images Hit paper breakdown → | 2018 | 419 |
| 2 | 2018 | 127 | |
| 3 | MaskGAN: Better Text Generation via Filling in the ____ | 2018 | 105 |
| 4 | Language GANs Falling Short | 2020 | 35 |
| 5 | 2020 | 33 | |
| 6 | Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step | 2018 | 31 |
| 7 | 2022 | 28 | |
| 8 | 2023 | 23 | |
| 9 | 2020 | 11 | |
| 10 | 2021 | 3 | |
| 11 | Revisiting ResNets: Improved Training and Scaling Strategies | 2021 | 2 |
About William Fedus
William Fedus is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science, Information Systems and Statistical and Nonlinear Physics, having authored 11 papers that have together received 817 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (3 papers), Domain Adaptation and Few-Shot Learning (2 papers), Artificial Intelligence in Games (2 papers), Digital Games and Media (2 papers), Advanced Neural Network Applications (2 papers), Complex Systems and Time Series Analysis (1 paper), Medical Image Segmentation Techniques (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Biophysics (270 citations), Media Technology (108 citations), Artificial Intelligence (391 citations), Computer Vision and Pattern Recognition (200 citations) and Structural Biology (8 citations). William Fedus has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Andrew M. Dai, Ian Goodfellow, Yoshua Bengio, D. Michael Ando, Piyush Goyal, Steven Finkbeiner, Andre Esteva, Kevan Shah, Scott Lipnick and Lee L. Rubin. Their work appears in journals such as Cell, Neural Information Processing Systems, Apollo (University of Cambridge), International Conference on Learning Representations and arXiv (Cornell University).
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.