Manuel Samuelides

905 citations
38 papers · 497 · h-index 13

Impact in

Papers in

Manuel Samuelides

34 papers receiving 468 citations

Peers

Manuel Samuelides
Comparison fields: 5 of 64
  • Statistical and Nonlinear Physics 184
  • Cognitive Neuroscience 251
  • Artificial Intelligence 164
  • Statistics, Probability and Uncertainty 34
  • Computational Mechanics 71
Replace Yanyang Xiao with:
Yanyang Xiao China
Tohru Ikeguchi Japan
Vince Lyzinski United States
S. Amari Japan
Sanya Mitaim United States
A. Passamante United States
Тимур Каримов Russia
Tetsuya Yoshinaga Japan
Ricardo Riaza Spain
Donniell E. Fishkind United States
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Citations per field
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Yanyang Xiao · 1×
Citations per year

Countries citing papers authored by Manuel Samuelides

Since Specialization
Citations

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

Fields of papers citing papers by Manuel Samuelides

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Manuel Samuelides, 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 Manuel Samuelides Line = papers co-authored together Manuel Samuelides links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199366
2 201264
3 199448
4 200444
5 201034
6 199833
7 200428
8 200125
9 200224
10 198619
11 200716
12 199415
13 200312
14 200211
15
Application of response surface methodology to stiffened \npanel optimization
20067
16 19967
17 19907
18 20055
19 20015
20 19955

About Manuel Samuelides

Manuel Samuelides is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Statistical and Nonlinear Physics, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 38 papers that have together received 497 indexed citations. Recurring topics across this work include Neural dynamics and brain function (15 papers), Neural Networks and Applications (13 papers), stochastic dynamics and bifurcation (7 papers), Image Retrieval and Classification Techniques (6 papers), Advanced Memory and Neural Computing (5 papers), Advanced Image and Video Retrieval Techniques (5 papers), Neural Networks Stability and Synchronization (3 papers) and Probabilistic and Robust Engineering Design (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (184 citations), Cognitive Neuroscience (251 citations), Artificial Intelligence (164 citations), Statistics, Probability and Uncertainty (34 citations) and Computational Mechanics (71 citations). Manuel Samuelides has collaborated with scholars based in France, United States and Belgium. Frequent co-authors include Bruno Cessac, B. Doyon, Mathias Quoy, Laurent Perrinet, Simon J. Thorpe, Denis Sipp, Peter J. Schmid, Stéphane Grihon, Nathalie Bartoli and Joseph Morlier. Their work appears in journals such as Neurocomputing, Acta Biotheoretica, Probability Theory and Related Fields, International Journal of Bifurcation and Chaos and Neural Processing Letters.

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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