Sara van de Geer

75 papers and 4.9k indexed citations i.

About

Sara van de Geer is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Sara van de Geer has authored 75 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Statistics and Probability, 24 papers in Artificial Intelligence and 17 papers in Computational Mechanics. Recurrent topics in Sara van de Geer’s work include Statistical Methods and Inference (56 papers), Bayesian Methods and Mixture Models (16 papers) and Sparse and Compressive Sensing Techniques (16 papers). Sara van de Geer is often cited by papers focused on Statistical Methods and Inference (56 papers), Bayesian Methods and Mixture Models (16 papers) and Sparse and Compressive Sensing Techniques (16 papers). Sara van de Geer collaborates with scholars based in Switzerland, The Netherlands and United States. Sara van de Geer's co-authors include Peter Bühlmann, Lukas Meier, Ya’acov Ritov, Enno Mammen, Arie Kapteyn, Huib van de Stadt, Nicolas Städler, Mohamed Hebiri, Philipp Rütimann and Massimiliano Pontil and has published in prestigious journals such as IEEE Transactions on Information Theory, The Review of Economics and Statistics and IEEE Transactions on Signal Processing.

In The Last Decade

Co-authorship network of co-authors of Sara van de Geer i

Fields of papers citing papers by Sara van de Geer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Sara van de Geer

Since Specialization
Citations

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