Jan Ramon
Impact in
- Artificial Intelligence top 2%
- Bayesian Modeling and Causal Inference
- Reinforcement Learning in Robotics
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- Rough Sets and Fuzzy Logic
- Computational Drug Discovery Methods
Papers in
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- Bayesian Modeling and Causal Inference 11
- Reinforcement Learning in Robotics 10
- Algorithms and Data Compression 6
- Evolutionary Algorithms and Applications 6
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- Data Mining Algorithms and Applications 21
- Co-authors
- Maurice Bruynooghe (28 shared papers)Luc De Raedt (7 shared papers)Hendrik Blockeel (30 shared papers)Kurt Driessens (8 shared papers)Fabián Güiza (9 shared papers)Geert Meyfroidt (8 shared papers)Tamás Horváth (3 shared papers)Leander Schietgat (9 shared papers)
- Journals
- Machine Learning (8 papers)Data Mining and Knowledge Discovery (5 papers)Journal of Controlled Release (2 papers)Best practice & research. Clinical anaesthesiology (1 paper)Theoretical Computer Science (1 paper)
- Partner nations
- BelgiumFranceNetherlands
In The Last Decade
Jan Ramon
88 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 148
- Artificial Intelligence 592
- Computational Theory and Mathematics 210
- Signal Processing 141
- Computer Vision and Pattern Recognition 228
- Information Systems 230
Countries citing papers authored by Jan Ramon
This map shows the geographic impact of Jan Ramon'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 Jan Ramon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Ramon more than expected).
Fields of papers citing papers by Jan Ramon
This network shows the impact of papers produced by Jan Ramon. 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 Jan Ramon. The network helps show where Jan Ramon may publish in the future.
Co-authors
The 25 scholars most cited alongside Jan Ramon, 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 101 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Multi instance neural networks | 2000 | 99 |
| 2 | 2015 | 99 | |
| 3 | Expressivity versus efficiency of graph kernels | 2003 | 85 |
| 4 | 2015 | 83 | |
| 5 | 2009 | 73 | |
| 6 | 2007 | 62 | |
| 7 | 2013 | 53 | |
| 8 | 2002 | 50 | |
| 9 | Hierarchical multi-classification | 2002 | 46 |
| 10 | 2001 | 45 | |
| 11 | 2013 | 41 | |
| 12 | 2006 | 38 | |
| 13 | 2010 | 36 | |
| 14 | 2011 | 33 | |
| 15 | Relational instance based regression for relational reinforcement learning | 2003 | 33 |
| 16 | 2006 | 26 | |
| 17 | 2018 | 25 | |
| 18 | 2010 | 24 | |
| 19 | Condensed representations for inductive logic programming | 2004 | 22 |
| 20 | Thesis: clustering and instance based learning in first order logic | 2002 | 21 |
About Jan Ramon
Jan Ramon is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Molecular Biology and Computer Vision and Pattern Recognition, having authored 101 papers that have together received 1.4k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (21 papers), Graph Theory and Algorithms (12 papers), Bayesian Modeling and Causal Inference (11 papers), Reinforcement Learning in Robotics (10 papers), Data Management and Algorithms (8 papers), Advanced Graph Theory Research (8 papers), Algorithms and Data Compression (6 papers) and Evolutionary Algorithms and Applications (6 papers). The work is most often cited by research in Artificial Intelligence (592 citations), Computational Theory and Mathematics (210 citations), Signal Processing (141 citations), Computer Vision and Pattern Recognition (228 citations) and Information Systems (230 citations). Jan Ramon has collaborated with scholars based in Belgium, France and Netherlands. Frequent co-authors include Maurice Bruynooghe, Luc De Raedt, Hendrik Blockeel, Kurt Driessens, Fabián Güiza, Geert Meyfroidt, Tamás Horváth, Leander Schietgat, Stefan Wrobel and Tom Croonenborghs. Their work appears in journals such as Machine Learning, Data Mining and Knowledge Discovery, Journal of Controlled Release, Best practice & research. Clinical anaesthesiology and Theoretical Computer Science.
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.