David L. Dowe
About
In The Last Decade
David L. Dowe
69 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 133
- Artificial Intelligence 471
- Clinical Psychology 232
- Cognitive Neuroscience 208
- Computational Theory and Mathematics 208
- Sociology and Political Science 147
Countries citing papers authored by David L. Dowe
This map shows the geographic impact of David L. Dowe'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 David L. Dowe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David L. Dowe more than expected).
Fields of papers citing papers by David L. Dowe
This network shows the impact of papers produced by David L. Dowe. 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 David L. Dowe. The network helps show where David L. Dowe may publish in the future.
Co-authorship network of co-authors of David L. Dowe
This figure shows the co-authorship network connecting the top 25 collaborators of David L. Dowe. A scholar is included among the top collaborators of David L. Dowe 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 David L. Dowe. David L. Dowe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 9 | |
| 6 | 9 | |
| 7 | Computer models solving intelligence test problems: progress and implications | 0 |
| 8 | 37 | |
| 9 | Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence: Papers from the Ray Solomonoff 85th Memorial Conference, ... / Lecture Notes in Artificial Intelligence | 1 |
| 10 | 3 | |
| 11 | A novel approach for modeling malaria incidence using complex categorical household data: The minimum message length (MML) method applied to Indonesian data | 3 |
| 12 | Turing machines and recursive Turing Tests | 1 |
| 13 | 74 | |
| 14 | The Turing Test | 21 |
| 15 | Unsupervised learning of Gamma mixture models using Minimum Message Length | 10 |
| 16 | Univariate Polynomial Inference by Monte Carlo Message Length Approximation | 8 |
| 17 | Message Length as an Effective Ockham’s Razor in Decision Tree Induction | 19 |
| 18 | Complexity and information-theoretic approaches to biology | 1 |
| 19 | Information, statistics and induction in science : proceedings of the conference, ISIS '96 : Melbourne, Australia, 20-23 August 1996 | 0 |
| 20 | Model selection in linear regression using the MML criterion | 6 |
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.