Milan Paluš

175 total papers · 6.1k total citations
95 papers, 4.3k citations indexed

About

Milan Paluš is a scholar working on Economics and Econometrics, Cognitive Neuroscience and Statistical and Nonlinear Physics. According to data from OpenAlex, Milan Paluš has authored 95 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Economics and Econometrics, 36 papers in Cognitive Neuroscience and 35 papers in Statistical and Nonlinear Physics. Recurrent topics in Milan Paluš's work include Complex Systems and Time Series Analysis (38 papers), Neural dynamics and brain function (33 papers) and Chaos control and synchronization (24 papers). Milan Paluš is often cited by papers focused on Complex Systems and Time Series Analysis (38 papers), Neural dynamics and brain function (33 papers) and Chaos control and synchronization (24 papers). Milan Paluš collaborates with scholars based in Czechia, United States and United Kingdom. Milan Paluš's co-authors include Martin Vejmelka, Kateřina Hlaváčková‐Schindler, Joydeep Bhattacharya, Dagmar Novotná, Jaroslav Hlinka, Aneta Stefanovska, David Hartman, Katalin Štěrbová, Z Hrnčíř and Vladimı́r Komárek and has published in prestigious journals such as Physical Review Letters, Nature Communications and Journal of Neuroscience.

In The Last Decade

Milan Paluš

91 papers receiving 4.2k citations

Hit Papers

Causality detection based... 2007 2026 2013 2019 2007 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
Milan Paluš 1.8k 1.1k 1.1k 738 660 95 4.3k
Jianbo Gao 885 0.5× 1.7k 1.5× 1.4k 1.3× 449 0.6× 756 1.1× 127 4.3k
Timothy Sauer 1.4k 0.8× 3.5k 3.1× 1.3k 1.2× 595 0.8× 1.7k 2.6× 113 7.5k
Yong Zou 731 0.4× 1.8k 1.6× 1.6k 1.4× 745 1.0× 1.2k 1.9× 160 4.9k
M. Carmen Romano 1.0k 0.6× 1.4k 1.2× 1.0k 0.9× 281 0.4× 933 1.4× 67 4.7k
Marko Thiel 865 0.5× 1.1k 0.9× 829 0.8× 246 0.3× 725 1.1× 39 3.6k
Donald B. Percival 1.1k 0.6× 461 0.4× 2.3k 2.1× 1.4k 1.9× 373 0.6× 110 10.4k
Kun Hu 1.8k 1.0× 1.1k 1.0× 2.3k 2.1× 377 0.5× 421 0.6× 192 9.3k
Joseph P. Zbilut 1.2k 0.6× 1.3k 1.2× 1.1k 1.0× 186 0.3× 647 1.0× 109 5.3k
Daniel T. Kaplan 936 0.5× 974 0.9× 920 0.8× 131 0.2× 466 0.7× 75 3.7k
Wen‐wen Tung 475 0.3× 834 0.7× 726 0.7× 787 1.1× 259 0.4× 59 2.8k

Countries citing papers authored by Milan Paluš

Since Specialization
Citations

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

Fields of papers citing papers by Milan Paluš

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Milan Paluš

This figure shows the co-authorship network connecting the top 25 collaborators of Milan Paluš. A scholar is included among the top collaborators of Milan Paluš 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 Milan Paluš. Milan Paluš 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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