Tobias Rydèn
- Artificial Intelligence top 2%
- Statistics and Probability top 1%
- Molecular Biology
- Radiology, Nuclear Medicine and Imaging top 5%
- Surgery
- Co-authors
- Éric MoulinesChristian P. RobertD. M. TitteringtonPeter BernhardtOlivier CappéLudger OverbeckMartijn van EssenMattias Höglund
- Topics
- Medical Imaging Techniques and Applications (15 papers)Radiomics and Machine Learning in Medical Imaging (10 papers)Bayesian Methods and Mixture Models (9 papers)
- Partner nations
- SwedenUnited StatesFrance
In The Last Decade
Tobias Rydèn
45 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Artificial Intelligence 654
- Statistics and Probability 413
- Molecular Biology 261
- Radiology, Nuclear Medicine and Imaging 257
- Surgery 200
Countries citing papers authored by Tobias Rydèn
This map shows the geographic impact of Tobias Rydèn'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 Tobias Rydèn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tobias Rydèn more than expected).
Fields of papers citing papers by Tobias Rydèn
This network shows the impact of papers produced by Tobias Rydèn. 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 Tobias Rydèn. The network helps show where Tobias Rydèn may publish in the future.
Co-authorship network of co-authors of Tobias Rydèn
This figure shows the co-authorship network connecting the top 25 collaborators of Tobias Rydèn. A scholar is included among the top collaborators of Tobias Rydèn 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 Tobias Rydèn. Tobias Rydèn 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 | 0 | |
| 3 | 0 | |
| 4 | 9 | |
| 5 | 59 | |
| 6 | 40 | |
| 7 | 54 | |
| 8 | 32 | |
| 9 | 7 | |
| 10 | 41 | |
| 11 | 224 | |
| 12 | Inference in Hidden Markov Modelsbreakdown → | 542 |
| 13 | 7 | |
| 14 | 11 | |
| 15 | 5 | |
| 16 | 6 | |
| 17 | 20 | |
| 18 | Linear filtering and state space representations of hidden Markov models | 0 |
| 19 | 0 | |
| 20 | 24 |
About Tobias Rydèn
Tobias Rydèn is a scholar working on Statistics and Probability, Health Informatics and Radiology, Nuclear Medicine and Imaging, having authored 55 papers that have together received 1.9k indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (15 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Bayesian Methods and Mixture Models (9 papers). The work is most often cited by research in Statistics and Probability (413 citations), Artificial Intelligence (654 citations) and Finance (185 citations). Tobias Rydèn has collaborated with scholars based in Sweden, United States and France. Frequent co-authors include Éric Moulines, Christian P. Robert, D. M. Titterington, Peter Bernhardt, Olivier Cappé, Ludger Overbeck, Martijn van Essen, Mattias Höglund, Vikram Krishnamurthy and Attila Frigyesi. Their work appears in journals such as The Journal of Chemical Physics, Blood 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.