Gábor J. Székely

103 papers and 4.6k indexed citations i.

About

Gábor J. Székely is a scholar working on Statistics and Probability, Artificial Intelligence and Finance. According to data from OpenAlex, Gábor J. Székely has authored 103 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Statistics and Probability, 23 papers in Artificial Intelligence and 14 papers in Finance. Recurrent topics in Gábor J. Székely’s work include Statistical Methods and Inference (19 papers), Advanced Statistical Methods and Models (15 papers) and Bayesian Methods and Mixture Models (12 papers). Gábor J. Székely is often cited by papers focused on Statistical Methods and Inference (19 papers), Advanced Statistical Methods and Models (15 papers) and Bayesian Methods and Mixture Models (12 papers). Gábor J. Székely collaborates with scholars based in Hungary, United States and Switzerland. Gábor J. Székely's co-authors include Maria L. Rizzo, Н. К. Бакиров, Tamás F. Móri, Guido Gerig, A. Kelemen, Dominic Edelmann, S. Gundy, Vijay K. Rohatgi, Richard M. Satava and Xiaoming Huo and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Scientific Reports.

In The Last Decade

Co-authorship network of co-authors of Gábor J. Székely i

Fields of papers citing papers by Gábor J. Székely

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Gábor J. Székely

Since Specialization
Citations

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