Danica J. Sutherland

14 papers and 221 indexed citations i.

About

Danica J. Sutherland is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistics and Probability. According to data from OpenAlex, Danica J. Sutherland has authored 14 papers receiving a total of 221 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Statistics and Probability. Recurrent topics in Danica J. Sutherland’s work include Statistical Methods and Inference (4 papers), Model Reduction and Neural Networks (3 papers) and Machine Learning and Algorithms (3 papers). Danica J. Sutherland is often cited by papers focused on Statistical Methods and Inference (4 papers), Model Reduction and Neural Networks (3 papers) and Machine Learning and Algorithms (3 papers). Danica J. Sutherland collaborates with scholars based in United States, United Kingdom and Canada. Danica J. Sutherland's co-authors include Jeff Schneider, Arthur Gretton, Barnabás Póczos, Michael Arbel, Mikołaj Bińkowski, Michelle Ntampaka, Hy Trac, Liang Xiong, Nicholas Battaglia and S. Fromenteau and has published in prestigious journals such as The Astrophysical Journal, Journal of Interprofessional Care and 2009 IEEE Conference on Computer Vision and Pattern Recognition.

In The Last Decade

Co-authorship network of co-authors of Danica J. Sutherland i

Fields of papers citing papers by Danica J. Sutherland

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Danica J. Sutherland. 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 Danica J. Sutherland. The network helps show where Danica J. Sutherland may publish in the future.

Countries citing papers authored by Danica J. Sutherland

Since Specialization
Citations

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