International Journal for Uncertainty Quantification

346 papers and 4.5k indexed citations i.

About

The 346 papers published in International Journal for Uncertainty Quantification in the last decades have received a total of 4.5k indexed citations. Papers published in International Journal for Uncertainty Quantification usually cover Statistics, Probability and Uncertainty (191 papers), Computational Theory and Mathematics (91 papers) and Artificial Intelligence (63 papers) specifically the topics of Probabilistic and Robust Engineering Design (189 papers), Advanced Multi-Objective Optimization Algorithms (71 papers) and Model Reduction and Neural Networks (45 papers). The most active scholars publishing in International Journal for Uncertainty Quantification are Harish Garg, Bruno Sudret, Loïc Le Gratiet, Josselin Garnier, Nancy Nancy, Joe Wiart, Roland Schöbi, Xindong Peng, Michael Eldred and James L. Beck.

In The Last Decade

Fields of papers published in International Journal for Uncertainty Quantification

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in International Journal for Uncertainty Quantification. 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 International Journal for Uncertainty Quantification.

Countries where authors publish in International Journal for Uncertainty Quantification

Since Specialization
Citations

This map shows the geographic impact of research published in International Journal for Uncertainty Quantification. 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 International Journal for Uncertainty Quantification with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites International Journal for Uncertainty Quantification 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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