M.R. Titchener

419 citations
25 papers · 304 · h-index 12

Impact in

Papers in

M.R. Titchener

24 papers receiving 275 citations

Peers

M.R. Titchener
Comparison fields: 5 of 50
  • Computational Theory and Mathematics 121
  • Artificial Intelligence 207
  • Computer Vision and Pattern Recognition 78
  • Computer Networks and Communications 69
  • Hardware and Architecture 18
Replace Kang Yang with:
Kang Yang China
Cuauhtémoc Mancillas-López Mexico
Shahram Etemadi Borujeni Iran
Lorenzo Sarti Italy
Mikael Goldmann Sweden
V. Arvind India
William A. Martin United States
Luděk Kučera Czechia
Yunlong He United States
V.B. Balakirsky Germany
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Citations per year

Countries citing papers authored by M.R. Titchener

Since Specialization
Citations

This map shows the geographic impact of M.R. Titchener'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 M.R. Titchener with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M.R. Titchener more than expected).

Fields of papers citing papers by M.R. Titchener

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.R. Titchener. 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 M.R. Titchener. The network helps show where M.R. Titchener may publish in the future.

Co-authors

The 19 scholars most cited alongside M.R. Titchener, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M.R. Titchener Line = papers co-authored together M.R. Titchener links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200150
2 199629
3 199724
4 198424
5 200421
6 198420
7 200219
8 200218
9 198615
10
How well do practical information measures estimate the Shannon entropy
200615
11 201112
12 199712
13 199710
14 19856
15
T-code compression for Arabic computational morphology
20036
16 19855
17 20013
18 20083
19 19993
20
A Comparison of Practical Information Measures
20052

About M.R. Titchener

M.R. Titchener is a scholar working on Artificial Intelligence, Molecular Biology, Computational Theory and Mathematics, Computer Networks and Communications and Statistical and Nonlinear Physics, having authored 25 papers that have together received 304 indexed citations. Recurring topics across this work include Algorithms and Data Compression (14 papers), DNA and Biological Computing (13 papers), Cellular Automata and Applications (8 papers), Computability, Logic, AI Algorithms (5 papers), Error Correcting Code Techniques (3 papers), Evolutionary Algorithms and Applications (2 papers), Advanced Data Storage Technologies (2 papers) and Fractal and DNA sequence analysis (2 papers). The work is most often cited by research in Computational Theory and Mathematics (121 citations), Artificial Intelligence (207 citations), Computer Vision and Pattern Recognition (78 citations), Computer Networks and Communications (69 citations) and Hardware and Architecture (18 citations). M.R. Titchener has collaborated with scholars based in New Zealand, Germany and Canada. Frequent co-authors include Ralf Steuer, W. Ebeling, Ulrich L. Günther, Jeffrey J. Hunter, Radu Nicolescu, Yang Jia, Ludwig Staiger, Peter Hunter, Bruce H. Smaill and Peter Hertling. Their work appears in journals such as Journal of Computational Chemistry, IEEE Transactions on Information Theory, Stochastics and Dynamics, Fundamenta Informaticae and Asia-Pacific Journal of Chemical 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.

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