Statistics and Computing

1.9k papers and 67.4k indexed citations i.

About

The 1.9k papers published in Statistics and Computing in the last decades have received a total of 67.4k indexed citations. Papers published in Statistics and Computing usually cover Statistics and Probability (1.1k papers), Artificial Intelligence (946 papers) and Statistics, Probability and Uncertainty (198 papers) specifically the topics of Statistical Methods and Inference (600 papers), Bayesian Methods and Mixture Models (562 papers) and Statistical Methods and Bayesian Inference (476 papers). The most active scholars publishing in Statistics and Computing are Ulrike von Luxburg, Bernhard Schölkopf, Alex Smola, Darrell Whitley, Christophe Andrieu, David J. Lunn, Nicky Best, Andrew C. Thomas, David J. Spiegelhalter and Arnaud Doucet.

In The Last Decade

Fields of papers published in Statistics and Computing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Statistics and Computing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Statistics and Computing.

Countries where authors publish in Statistics and Computing

Since Specialization
Citations

This map shows the geographic impact of research published in Statistics and Computing. 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 papers published in Statistics and Computing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Statistics and Computing 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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2025