Concha Bielza
Impact in
- Artificial Intelligence top 0.5%
- Bayesian Modeling and Causal Inference
- Text and Document Classification Technologies
- Machine Learning and Data Classification
- Metaheuristic Optimization Algorithms Research
Papers in
-
- Bayesian Modeling and Causal Inference 58
- Machine Learning and Data Classification 18
- Bayesian Methods and Mixture Models 17
- Data Stream Mining Techniques 10
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- Gene expression and cancer classification 9
- Co-authors
- Pedro Larrañaga (150 shared papers)Roberto Santana (15 shared papers)Hanen Borchani (5 shared papers)Gherardo Varando (7 shared papers)Vı́ctor Robles (9 shared papers)Rubén Armañanzas (14 shared papers)Hossein Karshenas (5 shared papers)José A. Lozano (7 shared papers)
- Journals
- International Journal of Approximate Reasoning (8 papers)Neurocomputing (7 papers)International Journal of Intelligent Systems (6 papers)PLoS ONE (4 papers)IEEE Access (4 papers)
- Partner nations
- SpainUnited StatesUnited Kingdom
In The Last Decade
Concha Bielza
176 papers receiving 4.3k citations
Concha Bielza's Hit Papers
Peers
Comparison fields: 5 of 195
- Artificial Intelligence 1.7k
- Statistics, Probability and Uncertainty 215
- Biophysics 152
- Computational Theory and Mathematics 393
- Management Science and Operations Research 273
Countries citing papers authored by Concha Bielza
This map shows the geographic impact of Concha Bielza'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 Concha Bielza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Concha Bielza more than expected).
Fields of papers citing papers by Concha Bielza
This network shows the impact of papers produced by Concha Bielza. 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 Concha Bielza. The network helps show where Concha Bielza may publish in the future.
Co-authors
The 25 scholars most cited alongside Concha Bielza, 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 183 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Machine learning in bioinformatics Hit paper breakdown → | 2006 | 542 |
| 2 | A survey on multi‐output regression Hit paper breakdown → | 2015 | 422 |
| 3 | 2014 | 179 | |
| 4 | 2008 | 142 | |
| 5 | 2011 | 133 | |
| 6 | 2013 | 110 | |
| 7 | 2011 | 88 | |
| 8 | 2017 | 88 | |
| 9 | 2013 | 87 | |
| 10 | 2014 | 85 | |
| 11 | 2013 | 77 | |
| 12 | 2012 | 69 | |
| 13 | 2010 | 68 | |
| 14 | 2008 | 67 | |
| 15 | 2021 | 67 | |
| 16 | 2013 | 67 | |
| 17 | 2012 | 66 | |
| 18 | 2018 | 58 | |
| 19 | 2013 | 55 | |
| 20 | 2010 | 54 |
About Concha Bielza
Concha Bielza is a scholar working on Artificial Intelligence, Molecular Biology, Cognitive Neuroscience, Management Science and Operations Research and Signal Processing, having authored 183 papers that have together received 4.5k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (58 papers), Neural dynamics and brain function (23 papers), Machine Learning and Data Classification (18 papers), Bayesian Methods and Mixture Models (17 papers), Cell Image Analysis Techniques (11 papers), Data Stream Mining Techniques (10 papers), Rough Sets and Fuzzy Logic (9 papers) and Gene expression and cancer classification (9 papers). The work is most often cited by research in Artificial Intelligence (1.7k citations), Statistics, Probability and Uncertainty (215 citations), Biophysics (152 citations), Computational Theory and Mathematics (393 citations) and Management Science and Operations Research (273 citations). Concha Bielza has collaborated with scholars based in Spain, United States and United Kingdom. Frequent co-authors include Pedro Larrañaga, Roberto Santana, Hanen Borchani, Gherardo Varando, Vı́ctor Robles, Rubén Armañanzas, Hossein Karshenas, José A. Lozano, Javier DeFelipe and Iñaki Inza. Their work appears in journals such as International Journal of Approximate Reasoning, Neurocomputing, International Journal of Intelligent Systems, PLoS ONE and IEEE Access.
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.