Vladimir Spokoiny

280 total papers · 5.5k total citations
107 papers, 2.7k citations indexed

About

Vladimir Spokoiny is a scholar working on Statistics and Probability, Finance and Artificial Intelligence. According to data from OpenAlex, Vladimir Spokoiny has authored 107 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Statistics and Probability, 21 papers in Finance and 19 papers in Artificial Intelligence. Recurrent topics in Vladimir Spokoiny's work include Statistical Methods and Inference (46 papers), Advanced Statistical Methods and Models (19 papers) and Financial Risk and Volatility Modeling (15 papers). Vladimir Spokoiny is often cited by papers focused on Statistical Methods and Inference (46 papers), Advanced Statistical Methods and Models (19 papers) and Financial Risk and Volatility Modeling (15 papers). Vladimir Spokoiny collaborates with scholars based in Germany, Russia and United States. Vladimir Spokoiny's co-authors include Yurii Nesterov, Jörg Polzehl, Joël L. Horowitz, Oleg Lepski, Anatoli Juditsky, Marian Hristache, Wolfgang Karl Härdle, Lutz Dümbgen, Enno Mammen and Albert N. Shiryaev and has published in prestigious journals such as Journal of the American Statistical Association, NeuroImage and Econometrica.

In The Last Decade

Vladimir Spokoiny

103 papers receiving 2.5k citations

Hit Papers

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Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Vladimir Spokoiny 1.3k 677 473 334 312 107 2.7k
A. B. Tsybakov 1.3k 1.1× 750 1.1× 337 0.7× 485 1.5× 194 0.6× 47 2.4k
M. Rosenblatt 1.4k 1.1× 842 1.2× 938 2.0× 204 0.6× 512 1.6× 78 4.2k
R. L. Eubank 2.4k 1.9× 696 1.0× 353 0.7× 298 0.9× 300 1.0× 84 4.1k
Jinchi Lv 2.3k 1.8× 1.0k 1.5× 329 0.7× 265 0.8× 317 1.0× 42 3.9k
Keith Knight 2.1k 1.6× 831 1.2× 673 1.4× 356 1.1× 493 1.6× 37 4.1k
Yuhong Yang 1.5k 1.2× 1.1k 1.6× 240 0.5× 225 0.7× 388 1.2× 123 3.9k
Axel Munk 1.4k 1.1× 421 0.6× 197 0.4× 351 1.1× 176 0.6× 164 3.1k
J. S. Marron 1.1k 0.9× 651 1.0× 188 0.4× 380 1.1× 237 0.8× 77 2.8k
Peter Hall 3.1k 2.4× 1.2k 1.7× 398 0.8× 230 0.7× 565 1.8× 108 4.5k
Elizaveta Levina 1.8k 1.4× 1.4k 2.1× 289 0.6× 619 1.9× 315 1.0× 53 4.6k

Countries citing papers authored by Vladimir Spokoiny

Since Specialization
Citations

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

Fields of papers citing papers by Vladimir Spokoiny

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vladimir Spokoiny

This figure shows the co-authorship network connecting the top 25 collaborators of Vladimir Spokoiny. A scholar is included among the top collaborators of Vladimir Spokoiny based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Vladimir Spokoiny. Vladimir Spokoiny is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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