Endika Bengoetxea
- Artificial Intelligence top 5%
- Computational Theory and Mathematics top 5%
- Computer Vision and Pattern Recognition top 10%
- Molecular Biology
- Industrial and Manufacturing Engineering top 5%
- Co-authors
- Pedro LarrañagaJosé A. LozanoIñaki InzaIsabelle BlochRoberto M. CésarGualberto Buela‐CasalBorja CalvoRubén Armañanzas
- Topics
- Bayesian Modeling and Causal Inference (5 papers)Metaheuristic Optimization Algorithms Research (4 papers)Evolutionary Algorithms and Applications (4 papers)
In The Last Decade
Endika Bengoetxea
17 papers receiving 903 citations
Peers
Comparison fields: 5 of 134
- Artificial Intelligence 434
- Computational Theory and Mathematics 166
- Computer Vision and Pattern Recognition 133
- Molecular Biology 92
- Industrial and Manufacturing Engineering 85
Countries citing papers authored by Endika Bengoetxea
This map shows the geographic impact of Endika Bengoetxea'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 Endika Bengoetxea with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Endika Bengoetxea more than expected).
Fields of papers citing papers by Endika Bengoetxea
This network shows the impact of papers produced by Endika Bengoetxea. 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 Endika Bengoetxea. The network helps show where Endika Bengoetxea may publish in the future.
Co-authorship network of co-authors of Endika Bengoetxea
This figure shows the co-authorship network connecting the top 25 collaborators of Endika Bengoetxea. A scholar is included among the top collaborators of Endika Bengoetxea based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Endika Bengoetxea. Endika Bengoetxea is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 30 | |
| 2 | 69 | |
| 3 | 7 | |
| 4 | Quality Assurance in Lifelong Learning. ENQA Workshop Report 18. | 0 |
| 5 | 14 | |
| 6 | 6 | |
| 7 | 72 | |
| 8 | 6 | |
| 9 | 47 | |
| 10 | 25 | |
| 11 | 10 | |
| 12 | 18 | |
| 13 | Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms (Studies in Fuzziness and Soft Computing) | 214 |
| 14 | 254 | |
| 15 | 53 | |
| 16 | Evolutionary computation based on Bayesian classifiers | 41 |
| 17 | 21 | |
| 18 | 57 |
About Endika Bengoetxea
Endika Bengoetxea is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 18 papers that have together received 944 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (5 papers), Metaheuristic Optimization Algorithms Research (4 papers) and Evolutionary Algorithms and Applications (4 papers). The work is most often cited by research in Artificial Intelligence (434 citations), Computational Theory and Mathematics (166 citations) and Industrial and Manufacturing Engineering (85 citations). Endika Bengoetxea has collaborated with scholars based in Spain, France and Brazil. Frequent co-authors include Pedro Larrañaga, José A. Lozano, Iñaki Inza, Isabelle Bloch, Roberto M. César, Gualberto Buela‐Casal, Borja Calvo, Rubén Armañanzas, Aymeric Perchant and Concha Bielza. Their work appears in journals such as Expert Systems with Applications, Pattern Recognition and Psychiatry Research.
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.