Andreas Loukas

1.8k citations
30 papers · 733 · h-index 13

Impact in

Papers in

Andreas Loukas

29 papers receiving 723 citations

Peers

Andreas Loukas
Comparison fields: 5 of 78
  • Statistical and Nonlinear Physics 287
  • Artificial Intelligence 502
  • Computational Mathematics 6
  • Computer Networks and Communications 200
  • Computer Vision and Pattern Recognition 77
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Citations per field
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Citations per year

Countries citing papers authored by Andreas Loukas

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Loukas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Andreas Loukas, 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 Andreas Loukas Line = papers co-authored together Andreas Loukas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016159
2 2017109
3 201973
4 201566
5 201765
6 201748
7 201930
8 201824
9 201624
10 201619
11 201413
12 201613
13 201412
14 201312
15 20178
16 20158
17 20157
18 20127
19
How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices
20175
20 20205

About Andreas Loukas

Andreas Loukas is a scholar working on Artificial Intelligence, Computer Networks and Communications, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition and Signal Processing, having authored 30 papers that have together received 733 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (14 papers), Complex Network Analysis Techniques (9 papers), Energy Efficient Wireless Sensor Networks (5 papers), Caching and Content Delivery (3 papers), Mobile Ad Hoc Networks (3 papers), Modular Robots and Swarm Intelligence (3 papers), Wireless Networks and Protocols (3 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (287 citations), Artificial Intelligence (502 citations), Computational Mathematics (6 citations), Computer Networks and Communications (200 citations) and Computer Vision and Pattern Recognition (77 citations). Andreas Loukas has collaborated with scholars based in Netherlands, Switzerland and Germany. Frequent co-authors include Geert Leus, Andrea Simonetto, Elvin Isufi, Nathanaël Perraudin, Benjamin Ricaud, Nicolas Tremblay, Marco Zúñiga, Koen Langendoen, Pascal Frossard and Dorina Thanou. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Signal Processing Letters, SIAM Journal on Discrete Mathematics, PLoS Computational Biology and Cell Systems.

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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