Random Matrices Theory and Application

185 papers and 1.0k indexed citations

About

The 185 papers published in Random Matrices Theory and Application in the last decades have received a total of 1.0k indexed citations. Papers published in Random Matrices Theory and Application usually cover Statistics and Probability (154 papers), Mathematical Physics (97 papers) and Discrete Mathematics and Combinatorics (61 papers) specifically the topics of Random Matrices and Applications (142 papers), Advanced Combinatorial Mathematics (61 papers) and Advanced Algebra and Geometry (61 papers). The most active scholars publishing in Random Matrices Theory and Application are Van Vu, Terence Tao, Zhidong Bai, Peter J. Forrester, Yang Chen, Jack W. Silverstein, Alexander Soshnikov, Tiefeng Jiang, Edgar Dobriban and Xiuyuan Cheng.

In The Last Decade

Random Matrices Theory and Application

156 papers receiving 959 citations

Fields of papers published in Random Matrices Theory and Application

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Random Matrices Theory and Application. 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 Random Matrices Theory and Application.

Countries where authors publish in Random Matrices Theory and Application

Since Specialization
Citations

This map shows the geographic impact of research published in Random Matrices Theory and Application. 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 Random Matrices Theory and Application with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Random Matrices Theory and Application 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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