Alberto Suárez

2.8k citations
67 papers · 1.9k · h-index 23

Impact in

Papers in

Alberto Suárez

64 papers receiving 1.8k citations

Peers

Alberto Suárez
Comparison fields: 5 of 144
  • Artificial Intelligence 1.0k
  • Management Science and Operations Research 261
  • Computer Vision and Pattern Recognition 311
  • Statistical and Nonlinear Physics 178
  • Finance 124
Replace Sandro Ridella with:
Sandro Ridella Italy
John E. Shore United States
Peter Harremoës Denmark
Bing Li China
Marco Locatelli Italy
Michel Deza France
Yaser S. Abu‐Mostafa United States
Michael Mascagni United States
Christian Berg Denmark
Flemming Topsøe Denmark
Alberto Suárez relative to Sandro Ridella Italy Sandro Ridella's profile →
Citations per field
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Citations per year

Countries citing papers authored by Alberto Suárez

Since Specialization
Citations

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

Fields of papers citing papers by Alberto Suárez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009224
2 1992192
3 1999119
4 2006117
5 199198
6 200992
7 200685
8 200682
9 200871
10 201070
11 200558
12 201846
13 201843
14 201440
15 201239
16 200837
17 201536
18 199135
19 201128
20 199624

About Alberto Suárez

Alberto Suárez is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Statistics and Probability, Computer Vision and Pattern Recognition and Finance, having authored 67 papers that have together received 1.9k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (14 papers), Neural Networks and Applications (12 papers), Face and Expression Recognition (10 papers), Advanced Thermodynamics and Statistical Mechanics (8 papers), Advanced Statistical Methods and Models (7 papers), Risk and Portfolio Optimization (7 papers), Theoretical and Computational Physics (6 papers) and Bayesian Methods and Mixture Models (5 papers). The work is most often cited by research in Artificial Intelligence (1.0k citations), Management Science and Operations Research (261 citations), Computer Vision and Pattern Recognition (311 citations), Statistical and Nonlinear Physics (178 citations) and Finance (124 citations). Alberto Suárez has collaborated with scholars based in Spain, United States and Belgium. Frequent co-authors include Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, R. Silbey, Rubén Ruiz-Torrubiano, Irwin Oppenheim, James F. Lutsko, José Miguel Hernández-Lobato, Nader Fathianpour, John Ross and Katharine L. C. Hunt. Their work appears in journals such as The Journal of Chemical Physics, Pattern Recognition, Neurocomputing, IEEE Transactions on Pattern Analysis and Machine Intelligence and International Journal of Machine Learning and Cybernetics.

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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