Rudi Cilibrasi
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 2%
- Molecular Biology
- Computational Theory and Mathematics top 2%
- Topics
- Algorithms and Data Compression (5 papers)Machine Learning in Bioinformatics (3 papers)Fractal and DNA sequence analysis (3 papers)
- Journals
- IEEE Transactions on Information TheoryPattern RecognitionIEEE Transactions on Knowledge and Data Engineering
- Partner nations
- NetherlandsAustralia
In The Last Decade
Rudi Cilibrasi
13 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 497
- Information Systems 438
- Molecular Biology 341
- Computational Theory and Mathematics 316
Countries citing papers authored by Rudi Cilibrasi
This map shows the geographic impact of Rudi Cilibrasi'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 Rudi Cilibrasi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rudi Cilibrasi more than expected).
Fields of papers citing papers by Rudi Cilibrasi
This network shows the impact of papers produced by Rudi Cilibrasi. 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 Rudi Cilibrasi. The network helps show where Rudi Cilibrasi may publish in the future.
Co-authorship network of co-authors of Rudi Cilibrasi
This figure shows the co-authorship network connecting the top 25 collaborators of Rudi Cilibrasi. A scholar is included among the top collaborators of Rudi Cilibrasi 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 Rudi Cilibrasi. Rudi Cilibrasi 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 | 18 | |
| 3 | 15 | |
| 4 | 32 | |
| 5 | Statistical inference through data compression | 31 |
| 6 | The Google Similarity Distancebreakdown → | 1086 |
| 7 | 20 | |
| 8 | 48 | |
| 9 | 21 | |
| 10 | Clustering by Compressionbreakdown → | 645 |
| 11 | Compression-based Stemmatology: A Study of the Legend of St. Henry of Finland | 3 |
| 12 | 130 | |
| 13 | Algorithm Clustering of Music | 3 |
About Rudi Cilibrasi
Rudi Cilibrasi is a scholar working on Signal Processing, Linguistics and Language and Artificial Intelligence, having authored 13 papers that have together received 2.1k indexed citations. Recurring topics across this work include Algorithms and Data Compression (5 papers), Machine Learning in Bioinformatics (3 papers) and Fractal and DNA sequence analysis (3 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Signal Processing (275 citations) and Computer Vision and Pattern Recognition (497 citations). Rudi Cilibrasi has collaborated with scholars based in Netherlands and Australia. Frequent co-authors include Paul Vitányi, Ronald de Wolf, Leo van Iersel, Steven Kelk, John Tromp, Petri Myllymäki and Teemu Roos. Their work appears in journals such as IEEE Transactions on Information Theory, Pattern Recognition and IEEE Transactions on Knowledge and Data Engineering.
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.