László Szeidl

50 papers receiving 1.1k citations

László Szeidl's Hit Papers

A serial approach to local stochastic weather models 1991 · 416 citations
4160+11+23Years since publication100200300400

Peers

László Szeidl
Comparison fields: 5 of 115
  • Computational Mathematics 124
  • Global and Planetary Change 406
  • Ecological Modeling 81
  • Nature and Landscape Conservation 177
  • Ecology, Evolution, Behavior and Systematics 205
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Alina Zare United States
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Citations per year

Countries citing papers authored by László Szeidl

Since Specialization
Citations

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

Fields of papers citing papers by László Szeidl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside László Szeidl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with László Szeidl Line = papers co-authored together László Szeidl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A serial approach to local stochastic weather models
Hit paper breakdown →
1991416
2 2006142
3 2009107
4 200959
5 200653
6 201249
7 200740
8 201236
9 200631
10 200226
11 202026
12 200026
13 202117
14 201916
15 201113
16 201112
17 201010
18 20137
19 20087
20 19876

About László Szeidl

László Szeidl is a scholar working on Management Information Systems, Computational Mathematics, Mathematical Physics, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 58 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Queuing Theory Analysis (13 papers), Tensor decomposition and applications (13 papers), Control Systems and Identification (6 papers), Stochastic processes and statistical mechanics (5 papers), Probability and Risk Models (5 papers), Ecology and Vegetation Dynamics Studies (5 papers), Image and Signal Denoising Methods (5 papers) and Species Distribution and Climate Change (4 papers). The work is most often cited by research in Computational Mathematics (124 citations), Global and Planetary Change (406 citations), Ecological Modeling (81 citations), Nature and Landscape Conservation (177 citations) and Ecology, Evolution, Behavior and Systematics (205 citations). László Szeidl has collaborated with scholars based in Hungary, Italy and Russia. Frequent co-authors include Peter Racsko, Mikhail A. Semenov, Carlo Ricotta, Péter Várlaki, Miklós Telek, Péter Bárányi, András Rövid, János Izsák, János Mika and Yeung Yam. Their work appears in journals such as Theoretical Population Biology, Environmental and Ecological Statistics, Acta Polytechnica Hungarica, Applied Mathematical Modelling and Methods in Ecology and Evolution.

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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