Elina Robeva

23 papers and 290 indexed citations i.

About

Elina Robeva is a scholar working on Computational Theory and Mathematics, Computational Mathematics and Artificial Intelligence. According to data from OpenAlex, Elina Robeva has authored 23 papers receiving a total of 290 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computational Theory and Mathematics, 8 papers in Computational Mathematics and 7 papers in Artificial Intelligence. Recurrent topics in Elina Robeva’s work include Tensor decomposition and applications (8 papers), Matrix Theory and Algorithms (6 papers) and Bayesian Modeling and Causal Inference (4 papers). Elina Robeva is often cited by papers focused on Tensor decomposition and applications (8 papers), Matrix Theory and Algorithms (6 papers) and Bayesian Modeling and Causal Inference (4 papers). Elina Robeva collaborates with scholars based in United States, Canada and Germany. Elina Robeva's co-authors include Jan Draisma, Anna Seigal, Sam Payne, Geoffrey Schiebinger, Benjamin Recht, Bernd Sturmfels, Emil Horobeţ, Luke Oeding, Caroline Uhler and Jan-Christian Hütter and has published in prestigious journals such as The Annals of Statistics, Advances in Mathematics and SIAM Journal on Matrix Analysis and Applications.

In The Last Decade

Co-authorship network of co-authors of Elina Robeva i

Fields of papers citing papers by Elina Robeva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Elina Robeva. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Elina Robeva. The network helps show where Elina Robeva may publish in the future.

Countries citing papers authored by Elina Robeva

Since Specialization
Citations

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