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 57
- Machine Learning and Data Classification 18
- Bayesian Methods and Mixture Models 17
- Neural Networks and Applications 11
- Data Stream Mining Techniques 10
- Co-authors
- Pedro LarrañagaRoberto SantanaHanen BorchaniGherardo VarandoVı́ctor RoblesRubén ArmañanzasHossein KarshenasJosé A. Lozano
- Journals
- International Journal of Approximate Reasoning (8 papers)Neurocomputing (7 papers)International Journal of Intelligent Systems (6 papers)Neuroinformatics (4 papers)IEEE Access (4 papers)
- Partner nations
- SpainUnited StatesUnited Kingdom
In The Last Decade
Concha Bielza
175 papers receiving 4.2k citations
Hit Papers
Peers
Comparison fields: 5 of 198
- Artificial Intelligence 1.8k
- Statistics, Probability and Uncertainty 220
- Biophysics 157
- Computational Theory and Mathematics 405
- Health Informatics 30
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 3 | |
| 2 | 2023 | 15 | |
| 3 | 2023 | 0 | |
| 4 | 2022 | 3 | |
| 5 | 2021 | 1 | |
| 6 | 2021 | 9 | |
| 7 | 2019 | 14 | |
| 8 | Learning Tractable Multidimensional Bayesian Network Classifiers | 2016 | 1 |
| 9 | Decision boundary for discrete Bayesian network classifiers | 2015 | 16 |
| 10 | 2015 | 11 | |
| 11 | 2014 | 10 | |
| 12 | 2014 | 12 | |
| 13 | Advances in artificial intelligence : 15th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2013 Madrid, Spain, September 17-20, 2013, proceedings | 2013 | 1 |
| 14 | 2013 | 6 | |
| 15 | 2013 | 14 | |
| 16 | 2013 | 17 | |
| 17 | 2011 | 88 | |
| 18 | 2011 | 131 | |
| 19 | Mateda-2.0: A MATLAB Package for the Implementation and Analysis of Estimation of Distribution Algorithms | 2010 | 1 |
| 20 | IctNeo system for jaundice management | 1998 | 1 |
About Concha Bielza
Concha Bielza is a scholar working on Artificial Intelligence, Statistics and Probability, Biophysics, Signal Processing and Management Science and Operations Research, having authored 180 papers that have together received 4.4k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (57 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 (12 papers), Neural Networks and Applications (11 papers), Gene expression and cancer classification (11 papers) and Data Stream Mining Techniques (10 papers). The work is most often cited by research in Artificial Intelligence (1.8k citations), Statistics, Probability and Uncertainty (220 citations), Biophysics (157 citations), Computational Theory and Mathematics (405 citations) and Health Informatics (30 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, Neuroinformatics 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.