T.J. Tjalkens
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 5%
- Computational Theory and Mathematics top 5%
- Signal Processing top 5%
- Topics
- Algorithms and Data Compression (15 papers)Advanced Data Compression Techniques (7 papers)Cellular Automata and Applications (6 papers)
- Journals
- IEEE Transactions on Information TheoryProblems of Information TransmissionData Archiving and Networked Services (DANS)
- Partner nations
- NetherlandsUnited StatesRussia
In The Last Decade
T.J. Tjalkens
19 papers receiving 663 citations
Hit Papers
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 574
- Computer Vision and Pattern Recognition 175
- Computer Networks and Communications 172
- Computational Theory and Mathematics 142
- Signal Processing 131
Countries citing papers authored by T.J. Tjalkens
This map shows the geographic impact of T.J. Tjalkens'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 T.J. Tjalkens with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T.J. Tjalkens more than expected).
Fields of papers citing papers by T.J. Tjalkens
This network shows the impact of papers produced by T.J. Tjalkens. 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 T.J. Tjalkens. The network helps show where T.J. Tjalkens may publish in the future.
Co-authorship network of co-authors of T.J. Tjalkens
This figure shows the co-authorship network connecting the top 25 collaborators of T.J. Tjalkens. A scholar is included among the top collaborators of T.J. Tjalkens 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 T.J. Tjalkens. T.J. Tjalkens is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | K-shot learning of acoustic context | 1 |
| 2 | 2 | |
| 3 | Classification with the CTW algorithm | 1 |
| 4 | Context-Tree Weighting and Maximizing: Processing Betas | 4 |
| 5 | 7 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | A parallel implementation of the CTW compression algorithm | 4 |
| 12 | Context-tree maximizing | 24 |
| 13 | Complexity reducing techniques for the CTW algorithm | 1 |
| 14 | Reflections on the prize paper: the context-tree weighting method (invited) | 3 |
| 15 | 14 | |
| 16 | 40 | |
| 17 | The context-tree weighting method: basic propertiesbreakdown → | 566 |
| 18 | 6 | |
| 19 | 17 | |
| 20 | 30 |
About T.J. Tjalkens
T.J. Tjalkens is a scholar working on Artificial Intelligence, Signal Processing and Computational Theory and Mathematics, having authored 20 papers that have together received 732 indexed citations. Recurring topics across this work include Algorithms and Data Compression (15 papers), Advanced Data Compression Techniques (7 papers) and Cellular Automata and Applications (6 papers). The work is most often cited by research in Artificial Intelligence (574 citations), Signal Processing (131 citations) and Hardware and Architecture (71 citations). T.J. Tjalkens has collaborated with scholars based in Netherlands, United States and Russia. Frequent co-authors include F.M.J. Willems, Jean‐Paul M. G. Linnartz, Tanya Ignatenko, Albert De Vries and Hongming Yang. Their work appears in journals such as IEEE Transactions on Information Theory, Problems of Information Transmission and Data Archiving and Networked Services (DANS).
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.