Eugene Lukács

1.5k citations
42 papers · 711 indexed · h-index 13
Topics
Functional Equations Stability Results (5 papers)Mathematical and Theoretical Analysis (3 papers)Advanced Statistical Methods and Models (3 papers)

In The Last Decade

Eugene Lukács

37 papers receiving 561 citations

Peers

Eugene Lukács
Comparison fields: 5 of 82
  • Statistics and Probability 238
  • Mathematical Physics 171
  • Artificial Intelligence 150
  • Applied Mathematics 141
  • Finance 140
Replace Yu. V. Linnik with:
Yu. V. Linnik United Kingdom
Carl-Gustav Esseen Sweden
Harold Ruben Canada
Heinz Bauer Germany
P. A. Meyer France
R. V. Chacon Canada
J. H. B. Kemperman United States
Gérard Letac France
Yu. V. Prokhorov Russia
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Citations per field
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Yu. V. Linnik · 1×
Citations per year

Countries citing papers authored by Eugene Lukács

Since Specialization
Citations

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

Fields of papers citing papers by Eugene Lukács

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eugene Lukács

This figure shows the co-authorship network connecting the top 25 collaborators of Eugene Lukács. A scholar is included among the top collaborators of Eugene Lukács 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 Eugene Lukács. Eugene Lukács is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 8
2 2
3 0
4 3
5 19
6 3
7 5
8 55
9 3
10 1
11 19
12 60
13
Recent Developments in the Theory of Characteristic Functions
6
14 32
15
Les fonctions caractéristiques analytiques
4
16
Certains tests indépendants de la distribution initiale
1
17 9
18 4
19 2
20 12

About Eugene Lukács

Eugene Lukács is a scholar working on Theoretical Computer Science, Statistics and Probability and Applied Mathematics, having authored 42 papers that have together received 711 indexed citations. Recurring topics across this work include Functional Equations Stability Results (5 papers), Mathematical and Theoretical Analysis (3 papers) and Advanced Statistical Methods and Models (3 papers). The work is most often cited by research in Statistics and Probability (238 citations), Mathematical Physics (171 citations) and Finance (140 citations). Eugene Lukács has collaborated with scholars based in United States, Austria and India. Frequent co-authors include E. P. King, R. G. Laha, Simeon M. Berman, Otto Szász, Vijay K. Rohatgi, Harald Cramér, Charles E. Land, Michael Orkin, Paul Slepian and F. S. Van Vleck. Their work appears in journals such as Journal of the American Statistical Association, Technometrics and Lecture notes in mathematics.

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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