Henrik Linusson
- Artificial Intelligence top 10%
- Building and Construction
- Statistics and Probability top 10%
- Control and Systems Engineering
- Computational Theory and Mathematics
- Co-authors
- Ulf JohanssonHenrik BoströmTuve LöfströmUlf NorinderThierry KogejLars CarlssonErnst AhlbergOla Engkvist
- Topics
- Machine Learning and Data Classification (11 papers)Imbalanced Data Classification Techniques (5 papers)Machine Learning and Algorithms (4 papers)
- Partner nations
- SwedenUnited KingdomPakistan
In The Last Decade
Henrik Linusson
14 papers receiving 252 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 129
- Building and Construction 39
- Statistics and Probability 39
- Control and Systems Engineering 34
- Computational Theory and Mathematics 34
Countries citing papers authored by Henrik Linusson
This map shows the geographic impact of Henrik Linusson'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 Henrik Linusson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Henrik Linusson more than expected).
Fields of papers citing papers by Henrik Linusson
This network shows the impact of papers produced by Henrik Linusson. 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 Henrik Linusson. The network helps show where Henrik Linusson may publish in the future.
Co-authorship network of co-authors of Henrik Linusson
This figure shows the co-authorship network connecting the top 25 collaborators of Henrik Linusson. A scholar is included among the top collaborators of Henrik Linusson 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 Henrik Linusson. Henrik Linusson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | Venn predictors for well-calibrated probability estimation trees | 2 |
| 5 | 11 | |
| 6 | On the Calibration of Aggregated Conformal Predictors | 18 |
| 7 | 22 | |
| 8 | Using Conformal Prediction to Prioritize Compound Synthesis in Drug Discovery | 3 |
| 9 | 24 | |
| 10 | 19 | |
| 11 | 2 | |
| 12 | 121 | |
| 13 | 8 | |
| 14 | MULTI-OUTPUT RANDOM FORESTS | 14 |
| 15 | 1 |
About Henrik Linusson
Henrik Linusson is a scholar working on Artificial Intelligence, Statistics and Probability and Computational Theory and Mathematics, having authored 15 papers that have together received 264 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (11 papers), Imbalanced Data Classification Techniques (5 papers) and Machine Learning and Algorithms (4 papers). The work is most often cited by research in Statistics and Probability (39 citations), Transportation (31 citations) and Artificial Intelligence (129 citations). Henrik Linusson has collaborated with scholars based in Sweden, United Kingdom and Pakistan. Frequent co-authors include Ulf Johansson, Henrik Boström, Tuve Löfström, Ulf Norinder, Thierry Kogej, Lars Carlsson, Ernst Ahlberg, Ola Engkvist, Rubén Buendía and Susanne Winiwarter. Their work appears in journals such as The Journal of Urology, Expert Systems with Applications and Neurocomputing.
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.