Natalya Pya

About

Natalya Pya is a scholar working on Statistics and Probability, Artificial Intelligence and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Natalya Pya has authored 7 papers receiving a total of 572 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Statistics and Probability, 2 papers in Artificial Intelligence and 1 paper in Atomic and Molecular Physics, and Optics. Recurrent topics in Natalya Pya’s work include Statistical Methods and Inference (4 papers), Statistical Methods and Bayesian Inference (3 papers) and Bayesian Methods and Mixture Models (2 papers). Natalya Pya is often cited by papers focused on Statistical Methods and Inference (4 papers), Statistical Methods and Bayesian Inference (3 papers) and Bayesian Methods and Mixture Models (2 papers). Natalya Pya collaborates with scholars based in Kazakhstan, United Kingdom and Germany. Natalya Pya's co-authors include Simon N. Wood, Benjamin Säfken, Matteo Fasiolo and Matthias Schmidt and has published in prestigious journals such as Journal of the American Statistical Association, Statistical Science and Statistics and Computing.

In The Last Decade

Co-authorship network of co-authors of Natalya Pya i

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Fields of papers citing papers by Natalya Pya

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Natalya Pya. 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 Natalya Pya. The network helps show where Natalya Pya may publish in the future.

Countries citing papers authored by Natalya Pya

Since Specialization

Citations

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