Computational Mathematics

12.4k papers and 256.3k indexed citations i.

About

12.4k papers covering Computational Mathematics have received a total of 256.3k indexed citations since 1950. Papers on subfields are most often about the specific topic of Tensor decomposition and applications, Matrix Theory and Algorithms and Sparse and Compressive Sensing Techniques and also cover the fields of Computational Theory and Mathematics, Computational Mechanics and Artificial Intelligence. Papers citing papers on subfields are usually about Computational Theory and Mathematics, Computational Mechanics and Artificial Intelligence. Some of the most active scholars covering Computational Mathematics are Tamara G. Kolda, Liqun Qi, Lieven De Lathauwer, Brett W. Bader, Rasmus Bro, Ivan Oseledets, J. C. Gower, J. Douglas Carroll, Anthony Biglan and Jih-Jie Chang.

In The Last Decade

Fields of papers citing papers about Computational Mathematics

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers covering Computational Mathematics. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers covering Computational Mathematics.

Countries where authors publish papers about Computational Mathematics

Since Specialization
Citations

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