Frank Stephan
- Computational Theory and Mathematics top 0.5%
- Artificial Intelligence top 2%
- Statistics and Probability top 2%
- Geometry and Topology top 5%
- Molecular Biology
- Co-authors
- Sanjay JainAndré NiesMartin KummerWolfgang MerkleBakhadyr KhoussainovSebastiaan A. TerwijnJohn CaseCarl G. Jockusch
- Topics
- Computability, Logic, AI Algorithms (126 papers)semigroups and automata theory (85 papers)Machine Learning and Algorithms (77 papers)
- Partner nations
- SingaporeGermanyUnited States
In The Last Decade
Frank Stephan
175 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 106
- Computational Theory and Mathematics 934
- Artificial Intelligence 673
- Statistics and Probability 175
- Geometry and Topology 152
- Molecular Biology 142
Countries citing papers authored by Frank Stephan
This map shows the geographic impact of Frank Stephan'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 Stephan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Stephan more than expected).
Fields of papers citing papers by Frank Stephan
This network shows the impact of papers produced by Frank Stephan. 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 Stephan. The network helps show where Frank Stephan may publish in the future.
Co-authorship network of co-authors of Frank Stephan
This figure shows the co-authorship network connecting the top 25 collaborators of Frank Stephan. A scholar is included among the top collaborators of Frank Stephan 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 Stephan. Frank Stephan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | Randomness and Initial Segment Complexity for Probability Measures. | 1 |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | Depth, Highness and DNR degrees | 5 |
| 7 | 1 | |
| 8 | AUTOMATIC FUNCTIONS, LINEAR TIME AND LEARNING ∗ | 8 |
| 9 | 40 | |
| 10 | 3 | |
| 11 | Consistent Partial Identification. | 1 |
| 12 | 2 | |
| 13 | 15 | |
| 14 | Enumerations of the Kolmogorov Function | 1 |
| 15 | Meta-S: A Strategy-Oriented Meta-Solver Framework. | 4 |
| 16 | 13 | |
| 17 | The Complexity of Odd$^A_n$ | 1 |
| 18 | 3 | |
| 19 | 4 | |
| 20 | Action de l'insuffisance thyroïdienne sur l'excrétion rénale de l'eau, du sodium et du potassium chez le rat. | 3 |
About Frank Stephan
Frank Stephan is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Geometry and Topology, having authored 201 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computability, Logic, AI Algorithms (126 papers), semigroups and automata theory (85 papers) and Machine Learning and Algorithms (77 papers). The work is most often cited by research in Computational Theory and Mathematics (934 citations), Statistics and Probability (175 citations) and Artificial Intelligence (673 citations). Frank Stephan has collaborated with scholars based in Singapore, Germany and United States. Frequent co-authors include Sanjay Jain, André Nies, Martin Kummer, Wolfgang Merkle, Bakhadyr Khoussainov, Sebastiaan A. Terwijn, John Case, Carl G. Jockusch, Efim Kinber and Gabriele Schackert. Their work appears in journals such as Biochemical and Biophysical Research Communications, Diabetologia and Life Sciences.
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.