Monte Carlo Methods and Applications

550 papers and 3.5k indexed citations i.

About

The 550 papers published in Monte Carlo Methods and Applications in the last decades have received a total of 3.5k indexed citations. Papers published in Monte Carlo Methods and Applications usually cover Finance (143 papers), Numerical Analysis (112 papers) and Statistics and Probability (102 papers) specifically the topics of Stochastic processes and financial applications (130 papers), Mathematical Approximation and Integration (95 papers) and Probabilistic and Robust Engineering Design (57 papers). The most active scholars publishing in Monte Carlo Methods and Applications are Karl K. Sabelfeld, Aurélien Alfonsi, Gilles Pagès, Jacques Printems, Bruno Tuffin, Vlad Bally, I. M. Sobol, O. Kurbanmuradov, Denis Talay and D. L. McLeish.

In The Last Decade

Fields of papers published in Monte Carlo Methods and Applications

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Monte Carlo Methods and Applications. 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 Monte Carlo Methods and Applications.

Countries where authors publish in Monte Carlo Methods and Applications

Since Specialization
Citations

This map shows the geographic impact of research published in Monte Carlo Methods and Applications. 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 Monte Carlo Methods and Applications with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Monte Carlo Methods and Applications 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