Frank Jensen
- Artificial Intelligence top 2%
- Management Science and Operations Research top 5%
- Signal Processing top 10%
- Statistics, Probability and Uncertainty top 5%
- Control and Systems Engineering top 10%
- Co-authors
- Finn V. JensenKristian G. OlesenStig Kjær AndersenSteffen L. LauritzenAnders L. MadsenUffe KjærulffMichael LangAntonio Salmerón
- Topics
- Bayesian Modeling and Causal Inference (7 papers)AI-based Problem Solving and Planning (3 papers)Rough Sets and Fuzzy Logic (2 papers)
In The Last Decade
Frank Jensen
9 papers receiving 645 citations
Peers
Comparison fields: 5 of 108
- Artificial Intelligence 531
- Management Science and Operations Research 129
- Signal Processing 95
- Statistics, Probability and Uncertainty 72
- Control and Systems Engineering 69
Countries citing papers authored by Frank Jensen
This map shows the geographic impact of Frank Jensen'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 Frank Jensen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Jensen more than expected).
Fields of papers citing papers by Frank Jensen
This network shows the impact of papers produced by Frank Jensen. 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 Frank Jensen. The network helps show where Frank Jensen may publish in the future.
Co-authorship network of co-authors of Frank Jensen
This figure shows the co-authorship network connecting the top 25 collaborators of Frank Jensen. A scholar is included among the top collaborators of Frank Jensen 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 Frank Jensen. Frank Jensen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 61 | |
| 2 | HUGIN - The Tool for Bayesian Networks and Influence Diagrams | 23 |
| 3 | 70 | |
| 4 | 163 | |
| 5 | Analysis in HUGIN of data conflict | 34 |
| 6 | HUGIN: a shell for building Bayesian belief universes for expert systems | 256 |
| 7 | HUGIN - a Shell for Building Belief Universes for Expert Systems | 28 |
| 8 | 82 | |
| 9 | 1 |
About Frank Jensen
Frank Jensen is a scholar working on Artificial Intelligence, Software and Computational Theory and Mathematics, having authored 9 papers that have together received 718 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (7 papers), AI-based Problem Solving and Planning (3 papers) and Rough Sets and Fuzzy Logic (2 papers). The work is most often cited by research in Artificial Intelligence (531 citations), Management Science and Operations Research (129 citations) and Statistics, Probability and Uncertainty (72 citations). Frank Jensen has collaborated with scholars based in Denmark, Finland and Spain. Frequent co-authors include Finn V. Jensen, Kristian G. Olesen, Stig Kjær Andersen, Steffen L. Lauritzen, Anders L. Madsen, Uffe Kjærulff, Michael Lang, Antonio Salmerón, Helge Langseth and Steen Andreassen. Their work appears in journals such as Knowledge-Based Systems, Statistics and Computing and Applied Artificial Intelligence.
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.