Willem Waegeman
- Ecological Modeling top 5%
- Artificial Intelligence top 2%
- Imbalanced Data Classification Techniques 10
- Machine Learning and Data Classification 9
- Bayesian Modeling and Causal Inference 9
- Text and Document Classification Technologies 8
- Biophysics top 2%
- Clinical Biochemistry top 5%
- Ecology top 5%
- Microbial Community Ecology and Physiology 8
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- Genomics and Phylogenetic Studies 10
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- Mycotoxins in Agriculture and Food 8
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- Multi-Criteria Decision Making 7
- Co-authors
- Bernard De BaetsEyke HüllermeierKrzysztof DembczyńskiWeiwei ChengPeter RubbensNico BoonLuc BoullartRuben Props
- Journals
- Nucleic Acids Research (2 papers)Nature Communications (1 paper)SHILAP Revista de lepidopterología (1 paper)
In The Last Decade
Willem Waegeman
104 papers receiving 2.9k citations
Peers
Comparison fields: 5 of 191
- Ecological Modeling 109
- Artificial Intelligence 715
- Biophysics 114
- Clinical Biochemistry 121
- Ecology 446
Countries citing papers authored by Willem Waegeman
This map shows the geographic impact of Willem Waegeman'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 Willem Waegeman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Willem Waegeman more than expected).
Fields of papers citing papers by Willem Waegeman
This network shows the impact of papers produced by Willem Waegeman. 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 Willem Waegeman. The network helps show where Willem Waegeman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Willem Waegeman, 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 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 8 | |
| 7 | 2021 | 21 | |
| 8 | 2020 | 21 | |
| 9 | Efficient Algorithms for Set-Valued Prediction in Multi-Class Classification. | 2019 | 3 |
| 10 | Discovering relationships in climate-vegetation dynamics using satellite data | 2016 | 3 |
| 11 | 2014 | 49 | |
| 12 | Plant disease prediction using data mining and machine learning: a case study on Fusarium head blight and deoxynivalenol content in winter wheat | 2013 | 1 |
| 13 | Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization | 2013 | 56 |
| 14 | Learning monadic and dyadic relations : three case studies in systems biology | 2012 | 1 |
| 15 | 2012 | 37 | |
| 16 | An Exact Algorithm for F-Measure Maximization | 2011 | 58 |
| 17 | From circular ordinal regression to multilabel classification | 2010 | 8 |
| 18 | On label dependence in multilabel classification | 2010 | 36 |
| 19 | From ranking to intransitive preference learning: rock-paper-scissors and beyond | 2009 | 2 |
| 20 | A Graph-theoretic Approach for Reducing One-versus-one Multi-class Classification to Ranking. International Workshop on Mining and Learning with Graphs | 2008 | 1 |
About Willem Waegeman
Willem Waegeman is a scholar working on Ecological Modeling, Artificial Intelligence and Biophysics, having authored 106 papers that have together received 3.0k indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (10 papers), Genomics and Phylogenetic Studies (10 papers), Machine Learning and Data Classification (9 papers), Bayesian Modeling and Causal Inference (9 papers), Microbial Community Ecology and Physiology (8 papers), Text and Document Classification Technologies (8 papers), Mycotoxins in Agriculture and Food (8 papers) and Multi-Criteria Decision Making (7 papers). The work is most often cited by research in Ecological Modeling (109 citations), Artificial Intelligence (715 citations) and Biophysics (114 citations). Willem Waegeman has collaborated with scholars based in Belgium, Germany and Finland. Frequent co-authors include Bernard De Baets, Eyke Hüllermeier, Krzysztof Dembczyński, Weiwei Cheng, Peter Rubbens, Nico Boon, Luc Boullart, Ruben Props, Niko E. C. Verhoest and Diego G. Miralles. Their work appears in journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.
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.