Sara Sabour

8 papers and 474 indexed citations i.

About

Sara Sabour is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Sara Sabour has authored 8 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 2 papers in Computational Mechanics. Recurrent topics in Sara Sabour’s work include Adversarial Robustness in Machine Learning (3 papers), Computer Graphics and Visualization Techniques (2 papers) and Advanced Neural Network Applications (2 papers). Sara Sabour is often cited by papers focused on Adversarial Robustness in Machine Learning (3 papers), Computer Graphics and Visualization Techniques (2 papers) and Advanced Neural Network Applications (2 papers). Sara Sabour collaborates with scholars based in United States, Canada and United Kingdom. Sara Sabour's co-authors include Geoffrey E. Hinton, Nicholas Frosst, David J. Fleet, Fartash Faghri, Yanshuai Cao, Yee Whye Teh, Adam R. Kosiorek, Andrea Tagliasacchi, Mohammad Norouzi and William Chan and has published in prestigious journals such as ACM Transactions on Graphics, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).

In The Last Decade

Co-authorship network of co-authors of Sara Sabour i

Fields of papers citing papers by Sara Sabour

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sara Sabour. 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 Sara Sabour. The network helps show where Sara Sabour may publish in the future.

Countries citing papers authored by Sara Sabour

Since Specialization
Citations

This map shows the geographic impact of Sara Sabour'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 Sara Sabour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara Sabour 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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