Communications in Mathematics and Statistics

317 papers and 3.0k indexed citations

About

The 317 papers published in Communications in Mathematics and Statistics in the last decades have received a total of 3.0k indexed citations. Papers published in Communications in Mathematics and Statistics usually cover Statistics and Probability (79 papers), Mathematical Physics (68 papers) and Applied Mathematics (68 papers) specifically the topics of Stochastic processes and financial applications (32 papers), Statistical Methods and Inference (32 papers) and Geometric Analysis and Curvature Flows (29 papers). The most active scholars publishing in Communications in Mathematics and Statistics are E Weinan, Bing Yu, Arnulf Jentzen, Jiequn Han, Alexander N. Skiba, Zhang Li, Xicheng Zhang, Mokhtar Hafayed, Savin Treanţă and Bhupendra Singh.

In The Last Decade

Communications in Mathematics and Statistics

256 papers receiving 2.8k citations

Countries where authors publish in Communications in Mathematics and Statistics

Since Specialization
Citations

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

Fields of papers published in Communications in Mathematics and Statistics

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Communications in Mathematics and Statistics. 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 Communications in Mathematics and Statistics.

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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