Antonio Salmerón
- Artificial Intelligence top 1%
- Bayesian Modeling and Causal Inference 62
- Bayesian Methods and Mixture Models 17
- Gaussian Processes and Bayesian Inference 10
- AI-based Problem Solving and Planning 8
- Machine Learning and Data Classification 8
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- Multi-Criteria Decision Making 8
- Statistics and Probability top 5%
- Signal Processing top 5%
- Data Management and Algorithms 19
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- Data Mining Algorithms and Applications 11
- Co-authors
- Rafael RumíPedro A. AguileraAntonio FernándezRosa FernándezSerafı́n MoralHelge LangsethThomas D. NielsenFabio Stella
- Cited by
- Artificial IntelligenceStatistics, Probability and UncertaintyManagement Science and Operations Research
In The Last Decade
Antonio Salmerón
84 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Artificial Intelligence 835
- Statistics, Probability and Uncertainty 143
- Management Science and Operations Research 227
- Statistics and Probability 120
- Signal Processing 149
Countries citing papers authored by Antonio Salmerón
This map shows the geographic impact of Antonio Salmerón'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 Antonio Salmerón with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antonio Salmerón more than expected).
Fields of papers citing papers by Antonio Salmerón
This network shows the impact of papers produced by Antonio Salmerón. 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 Antonio Salmerón. The network helps show where Antonio Salmerón may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Antonio Salmerón, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 2 | |
| 5 | 2023 | 1 | |
| 6 | 2021 | 3 | |
| 7 | 2021 | 8 | |
| 8 | 2020 | 2 | |
| 9 | 2019 | 156 | |
| 10 | 2013 | 20 | |
| 11 | 2011 | 48 | |
| 12 | 2011 | 2 | |
| 13 | Conditional Gaussian Probabilistic Decision Graphs | 2010 | 2 |
| 14 | El Clasificador Grafo de Decisión Probabilístico | 2007 | 1 |
| 15 | Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials | 2006 | 4 |
| 16 | Dynamic importance sampling in Bayesian networks using factorisation of probability trees. | 2006 | 2 |
| 17 | 2005 | 40 | |
| 18 | Advances in Bayesian Networks (Studies in Fuzziness and Soft Computing, V. 146) | 2004 | 4 |
| 19 | Estimating mixtures of truncated exponentials from data | 2002 | 15 |
| 20 | Towards an Operational Interpretation of Fuzzy Measures. | 1999 | 2 |
About Antonio Salmerón
Antonio Salmerón is a scholar working on Artificial Intelligence, Signal Processing and Management Science and Operations Research, having authored 88 papers that have together received 1.6k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (62 papers), Data Management and Algorithms (19 papers), Bayesian Methods and Mixture Models (17 papers), Data Mining Algorithms and Applications (11 papers), Gaussian Processes and Bayesian Inference (10 papers), Multi-Criteria Decision Making (8 papers), AI-based Problem Solving and Planning (8 papers) and Machine Learning and Data Classification (8 papers). The work is most often cited by research in Artificial Intelligence (835 citations), Statistics, Probability and Uncertainty (143 citations) and Management Science and Operations Research (227 citations). Antonio Salmerón has collaborated with scholars based in Spain, Denmark and Norway. Frequent co-authors include Rafael Rumí, Pedro A. Aguilera, Antonio Fernández, Rosa Fernández, Serafı́n Moral, Helge Langseth, Thomas D. Nielsen, Fabio Stella, Mauro Scanagatta and Andrés Cano. Their work appears in journals such as International Journal of Production Economics, BMC Genomics and Decision Support Systems.
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.