Jeffrey De Fauw

About

Jeffrey De Fauw is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jeffrey De Fauw has authored 4 papers receiving a total of 147 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 2 papers in Artificial Intelligence and 1 paper in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jeffrey De Fauw’s work include Generative Adversarial Networks and Image Synthesis (1 paper), Multimodal Machine Learning Applications (1 paper) and Image Processing and 3D Reconstruction (1 paper). Jeffrey De Fauw is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (1 paper), Multimodal Machine Learning Applications (1 paper) and Image Processing and 3D Reconstruction (1 paper). Jeffrey De Fauw collaborates with scholars based in United States, United Kingdom and Germany. Jeffrey De Fauw's co-authors include Sander Dieleman, Koray Kavukcuoglu, Klaus Maier‐Hein, S. M. Ali Eslami, Joseph R. Ledsam, Simon Köhl, Danilo Jimenez Rezende, Bernardino Romera‐Paredes, Clemens Meyer and Olaf Ronneberger and has published in prestigious journals such as Investigative Ophthalmology & Visual Science, arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Co-authorship network of co-authors of Jeffrey De Fauw i

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Fields of papers citing papers by Jeffrey De Fauw

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey De Fauw. 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 Jeffrey De Fauw. The network helps show where Jeffrey De Fauw may publish in the future.

Countries citing papers authored by Jeffrey De Fauw

Since Specialization

Citations

This map shows the geographic impact of Jeffrey De Fauw'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 Jeffrey De Fauw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffrey De Fauw more than expected).

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.

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