U. Dieter
Impact in
- Statistics and Probability top 2%
- Numerical Analysis top 5%
- Mathematical Approximation and Integration
Papers in
-
- Bayesian Methods and Mixture Models 7
- Algorithms and Data Compression 5
-
- Blind Source Separation Techniques 3
- Co-authors
- Joachim Ahrens (14 shared papers)A Gächter (1 shared paper)Karl Stoffel (1 shared paper)Gwidon Stachowiak (1 shared paper)Markus S. Kuster (1 shared paper)Georg Ch. Pflug (1 shared paper)
- Journals
- Computing (5 papers)Mathematics of Computation (4 papers)ACM Transactions on Mathematical Software (3 papers)Communications of the ACM (3 papers)Journal für die reine und angewandte Mathematik (Crelles Journal) (2 papers)
- Partner nations
- AustriaGermanyUnited States
In The Last Decade
U. Dieter
28 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 118
- Statistics and Probability 169
- Numerical Analysis 98
- Algebra and Number Theory 79
- Epidemiology 339
- Discrete Mathematics and Combinatorics 35
Countries citing papers authored by U. Dieter
This map shows the geographic impact of U. Dieter'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 U. Dieter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites U. Dieter more than expected).
Fields of papers citing papers by U. Dieter
This network shows the impact of papers produced by U. Dieter. 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 U. Dieter. The network helps show where U. Dieter may publish in the future.
Co-authors
The 6 scholars most cited alongside U. Dieter, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 498 | |
| 2 | 1974 | 215 | |
| 3 | 1972 | 91 | |
| 4 | 1982 | 75 | |
| 5 | 1982 | 55 | |
| 6 | 1973 | 45 | |
| 7 | 1970 | 44 | |
| 8 | 1975 | 44 | |
| 9 | 1980 | 40 | |
| 10 | 1966 | 29 | |
| 11 | 1984 | 24 | |
| 12 | 1971 | 23 | |
| 13 | 1989 | 20 | |
| 14 | 1988 | 19 | |
| 15 | 1957 | 19 | |
| 16 | 1971 | 18 | |
| 17 | 1983 | 18 | |
| 18 | 1959 | 16 | |
| 19 | 1985 | 15 | |
| 20 | 1982 | 14 |
About U. Dieter
U. Dieter is a scholar working on Artificial Intelligence, Signal Processing, Computational Theory and Mathematics, Numerical Analysis and Algebra and Number Theory, having authored 31 papers that have together received 1.4k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (7 papers), Algorithms and Data Compression (5 papers), Mathematical Approximation and Integration (3 papers), Analytic Number Theory Research (3 papers), Scientific Research and Discoveries (3 papers), Blind Source Separation Techniques (3 papers), Computability, Logic, AI Algorithms (2 papers) and Advanced Mathematical Identities (2 papers). The work is most often cited by research in Statistics and Probability (169 citations), Numerical Analysis (98 citations), Algebra and Number Theory (79 citations), Epidemiology (339 citations) and Discrete Mathematics and Combinatorics (35 citations). U. Dieter has collaborated with scholars based in Austria, Germany and United States. Frequent co-authors include Joachim Ahrens, A Gächter, Karl Stoffel, Gwidon Stachowiak, Markus S. Kuster and Georg Ch. Pflug. Their work appears in journals such as Computing, Mathematics of Computation, ACM Transactions on Mathematical Software, Communications of the ACM and Journal für die reine und angewandte Mathematik (Crelles Journal).
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.