Jan Ramon
Impact in
- Artificial Intelligence top 1%
- Bayesian Modeling and Causal Inference
- Reinforcement Learning in Robotics
- Logic, Reasoning, and Knowledge
- Semantic Web and Ontologies
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- Rough Sets and Fuzzy Logic
Papers in
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- Bayesian Modeling and Causal Inference 18
- Reinforcement Learning in Robotics 16
- Evolutionary Algorithms and Applications 11
- Logic, Reasoning, and Knowledge 9
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- Data Mining Algorithms and Applications 32
- Co-authors
- Maurice Bruynooghe (36 shared papers)Hendrik Blockeel (42 shared papers)Kurt Driessens (13 shared papers)Luc De Raedt (11 shared papers)Tom Croonenborghs (17 shared papers)Tamás Horváth (5 shared papers)Daan Fierens (12 shared papers)Fabián Güiza (9 shared papers)
In The Last Decade
Jan Ramon
123 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 155
- Artificial Intelligence 1.2k
- Computational Theory and Mathematics 428
- Signal Processing 257
- Information Systems 452
- Computer Vision and Pattern Recognition 354
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 136 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Multi instance neural networks | 2000 | 120 |
| 2 | 2015 | 114 | |
| 3 | Expressivity versus efficiency of graph kernels | 2003 | 105 |
| 4 | 2002 | 91 | |
| 5 | 2015 | 87 | |
| 6 | 2009 | 82 | |
| 7 | 2007 | 71 | |
| 8 | 2001 | 67 | |
| 9 | Hierarchical multi-classification | 2002 | 60 |
| 10 | 2001 | 60 | |
| 11 | 2006 | 55 | |
| 12 | 2007 | 55 | |
| 13 | 2013 | 54 | |
| 14 | 2009 | 52 | |
| 15 | 2006 | 47 | |
| 16 | 2013 | 45 | |
| 17 | Relational instance based regression for relational reinforcement learning | 2003 | 45 |
| 18 | 1998 | 43 | |
| 19 | 2005 | 43 | |
| 20 | Condensed representations for inductive logic programming | 2004 | 38 |
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 136 papers that have together received 2.2k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (32 papers), Bayesian Modeling and Causal Inference (18 papers), Graph Theory and Algorithms (16 papers), Reinforcement Learning in Robotics (16 papers), Data Management and Algorithms (11 papers), Evolutionary Algorithms and Applications (11 papers), Advanced Graph Theory Research (11 papers) and Logic, Reasoning, and Knowledge (9 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Computational Theory and Mathematics (428 citations), Signal Processing (257 citations), Information Systems (452 citations) and Computer Vision and Pattern Recognition (354 citations). Jan Ramon has collaborated with scholars based in Belgium, Germany and France. Frequent co-authors include Maurice Bruynooghe, Hendrik Blockeel, Kurt Driessens, Luc De Raedt, Tom Croonenborghs, Tamás Horváth, Daan Fierens, Fabián Güiza, Geert Meyfroidt and Stefan Wrobel. Their work appears in journals such as Machine Learning, Data Mining and Knowledge Discovery, Lecture notes in computer science, Journal of Controlled Release and Bioinformatics.
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.