Fernando Soler Toscano
Impact in
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- Computability, Logic, AI Algorithms
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
Papers in
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- Logic, Reasoning, and Knowledge 8
- Evolutionary Algorithms and Applications 7
- Semantic Web and Ontologies 5
- Logic, programming, and type systems 4
- Algorithms and Data Compression 4
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- Computability, Logic, AI Algorithms 12
- Co-authors
- Héctor Zenil (13 shared papers)Nicolas Gauvrit (9 shared papers)Jean‐Paul Delahaye (5 shared papers)Vasilis Dakos (1 shared paper)José A. Langa (7 shared papers)Henrik Singmann (1 shared paper)Kamaludin Dingle (2 shared papers)Ard A. Louis (2 shared papers)
In The Last Decade
Fernando Soler Toscano
35 papers receiving 427 citations
Peers
Comparison fields: 5 of 89
- Computational Theory and Mathematics 148
- Cognitive Neuroscience 109
- Artificial Intelligence 159
- General Decision Sciences 8
- Statistics and Probability 29
Countries citing papers authored by Fernando Soler Toscano
This map shows the geographic impact of Fernando Soler Toscano'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 Fernando Soler Toscano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Soler Toscano more than expected).
Fields of papers citing papers by Fernando Soler Toscano
This network shows the impact of papers produced by Fernando Soler Toscano. 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 Fernando Soler Toscano. The network helps show where Fernando Soler Toscano may publish in the future.
Co-authors
The 25 scholars most cited alongside Fernando Soler Toscano, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1Calculating Kolmogorov Complexity from the Output Frequency Distributions of Small Turing Machines | 2014 | 82 |
| 2 | 2015 | 38 | |
| 3 | 2013 | 35 | |
| 4 | 2016 | 35 | |
| 5 | 2014 | 31 | |
| 6 | 2015 | 28 | |
| 7 | 2017 | 26 | |
| 8 | 2018 | 23 | |
| 9 | 2014 | 18 | |
| 10 | 2013 | 18 | |
| 11 | 2013 | 10 | |
| 12 | 2017 | 9 | |
| 13 | 2013 | 9 | |
| 14 | 2019 | 9 | |
| 15 | 2017 | 8 | |
| 16 | 2011 | 7 | |
| 17 | 2024 | 5 | |
| 18 | 2022 | 5 | |
| 19 | 2013 | 5 | |
| 20 | 2013 | 5 |
About Fernando Soler Toscano
Fernando Soler Toscano is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Cognitive Neuroscience, Statistical and Nonlinear Physics and Electrical and Electronic Engineering, having authored 35 papers that have together received 441 indexed citations. Recurring topics across this work include Computability, Logic, AI Algorithms (12 papers), Logic, Reasoning, and Knowledge (8 papers), Evolutionary Algorithms and Applications (7 papers), Semantic Web and Ontologies (5 papers), Neural dynamics and brain function (5 papers), Logic, programming, and type systems (4 papers), Algorithms and Data Compression (4 papers) and graph theory and CDMA systems (3 papers). The work is most often cited by research in Computational Theory and Mathematics (148 citations), Cognitive Neuroscience (109 citations), Artificial Intelligence (159 citations), General Decision Sciences (8 citations) and Statistics and Probability (29 citations). Fernando Soler Toscano has collaborated with scholars based in Spain, France and Sweden. Frequent co-authors include Héctor Zenil, Nicolas Gauvrit, Jean‐Paul Delahaye, Vasilis Dakos, José A. Langa, Henrik Singmann, Kamaludin Dingle, Ard A. Louis, Fernando R. Velázquez–Quesada and José R. Portillo. Their work appears in journals such as Logic Journal of IGPL, PLoS Computational Biology, Behavior Research Methods, Designs Codes and Cryptography and Journal of Logic Language and Information.
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.