Luc De Raedt
- Artificial Intelligence top 0.1%
- Information Systems top 0.2%
- Computational Theory and Mathematics top 0.2%
- Signal Processing top 0.5%
- Computer Networks and Communications top 1%
- Co-authors
- Stephen MuggletonSašo DžeroskiHannu ToivonenAngelika KimmigStefan WrobelKristian KerstingStefan KrämerMaurice Bruynooghe
- Topics
- Data Mining Algorithms and Applications (62 papers)Bayesian Modeling and Causal Inference (62 papers)Logic, Reasoning, and Knowledge (58 papers)
In The Last Decade
Luc De Raedt
257 papers receiving 6.2k citations
Hit Papers
Peers
Comparison fields: 5 of 203
- Artificial Intelligence 4.4k
- Information Systems 1.7k
- Computational Theory and Mathematics 1.5k
- Signal Processing 850
- Computer Networks and Communications 806
Countries citing papers authored by Luc De Raedt
This map shows the geographic impact of Luc De Raedt'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 Luc De Raedt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luc De Raedt more than expected).
Fields of papers citing papers by Luc De Raedt
This network shows the impact of papers produced by Luc De Raedt. 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 Luc De Raedt. The network helps show where Luc De Raedt may publish in the future.
Co-authorship network of co-authors of Luc De Raedt
This figure shows the co-authorship network connecting the top 25 collaborators of Luc De Raedt. A scholar is included among the top collaborators of Luc De Raedt based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Luc De Raedt. Luc De Raedt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 7 | |
| 3 | 7 | |
| 4 | How to Exploit Structure while Solving Weighted Model Integration Problems. | 3 |
| 5 | Inducing probabilistic relational rules from probabilistic examples | 28 |
| 6 | 22 | |
| 7 | 87 | |
| 8 | 4 | |
| 9 | Logical and Relational Learning: From ILP to MRDM (Cognitive Technologies) | 47 |
| 10 | r-grams: relational grams | 3 |
| 11 | kFOIL: learning simple relational kernels | 46 |
| 12 | Constraint-based mining and inductive databases : European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004 : revised selected papers | 1 |
| 13 | Proceedings, Twenty-Second International Conference on Machine Learning | 22 |
| 14 | Logical Hidden Markov Models (Extended Abstract) | 1 |
| 15 | Feature Construction with Version Spaces for Biochemical Applications | 42 |
| 16 | Frequent query discovery: a unifying ILP approach to association rule mining | 2 |
| 17 | 1 | |
| 18 | 33 | |
| 19 | Some Thoughts on inverse resolution | 1 |
| 20 | Towards friendly concept-learners | 13 |
About Luc De Raedt
Luc De Raedt is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems, having authored 279 papers that have together received 6.8k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (62 papers), Bayesian Modeling and Causal Inference (62 papers) and Logic, Reasoning, and Knowledge (58 papers). The work is most often cited by research in Artificial Intelligence (4.4k citations), Computational Theory and Mathematics (1.5k citations) and Signal Processing (850 citations). Luc De Raedt has collaborated with scholars based in Belgium, Germany and Italy. Frequent co-authors include Stephen Muggleton, Sašo Džeroski, Hannu Toivonen, Angelika Kimmig, Stefan Wrobel, Kristian Kersting, Stefan Krämer, Maurice Bruynooghe, Siegfried Nijssen and Christoph Helma. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and Cancer Research.
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.