Bernhard Radke
Impact in
- Signal Processing top 5%
- Data Management and Algorithms
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- Advanced Database Systems and Queries
Papers in
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- Data Management and Algorithms 6
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- Advanced Database Systems and Queries 5
- Co-authors
- Thomas Neumann (6 shared papers)Alfons Kemper (4 shared papers)Viktor Leis (4 shared papers)Andrey Gubichev (2 shared papers)Peter Boncz (3 shared papers)Atanas Mirchev (1 shared paper)Andreas Kipf (2 shared papers)Thomas Kipf (2 shared papers)
- Journals
- The VLDB Journal (1 paper)Zenodo (CERN European Organization for Nuclear Research) (1 paper)Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands (2 papers)Conference on Innovative Data Systems Research (1 paper)
- Partner nations
- GermanyNetherlands
In The Last Decade
Bernhard Radke
6 papers receiving 207 citations
Peers
Comparison fields: 5 of 18
- Signal Processing 142
- Computer Networks and Communications 157
- Artificial Intelligence 98
- Management Science and Operations Research 33
- Computer Vision and Pattern Recognition 41
Countries citing papers authored by Bernhard Radke
This map shows the geographic impact of Bernhard Radke'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 Bernhard Radke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernhard Radke more than expected).
Fields of papers citing papers by Bernhard Radke
This network shows the impact of papers produced by Bernhard Radke. 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 Bernhard Radke. The network helps show where Bernhard Radke may publish in the future.
Co-authors
The 9 scholars most cited alongside Bernhard Radke, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 86 | |
| 2 | Cardinality Estimation Done Right: Index-Based Join Sampling. | 2017 | 46 |
| 3 | 2018 | 37 | |
| 4 | 2019 | 21 | |
| 5 | Learned Cardinalities: Estimating Correlated Joins with Deep Learning | 2018 | 14 |
| 6 | 2020 | 7 | |
| 7 | 2019 | 0 |
About Bernhard Radke
Bernhard Radke is a scholar working on Signal Processing, Computer Networks and Communications, Artificial Intelligence, Information Systems and Molecular Biology, having authored 7 papers that have together received 211 indexed citations. Recurring topics across this work include Data Management and Algorithms (6 papers), Advanced Database Systems and Queries (5 papers), Metabolism and Genetic Disorders (1 paper), Advanced Image and Video Retrieval Techniques (1 paper), Metabolism, Diabetes, and Cancer (1 paper), Semantic Web and Ontologies (1 paper), Bayesian Modeling and Causal Inference (1 paper) and Data Stream Mining Techniques (1 paper). The work is most often cited by research in Signal Processing (142 citations), Computer Networks and Communications (157 citations), Artificial Intelligence (98 citations), Management Science and Operations Research (33 citations) and Computer Vision and Pattern Recognition (41 citations). Bernhard Radke has collaborated with scholars based in Germany and Netherlands. Frequent co-authors include Thomas Neumann, Alfons Kemper, Viktor Leis, Andrey Gubichev, Peter Boncz, Atanas Mirchev, Andreas Kipf, Thomas Kipf and Jonas Müller. Their work appears in journals such as The VLDB Journal, Zenodo (CERN European Organization for Nuclear Research), Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands and Conference on Innovative Data Systems Research.
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.