David L. Dowe

3.0k total citations
78 papers, 1.2k citations indexed

About

David L. Dowe is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, David L. Dowe has authored 78 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 19 papers in Computational Theory and Mathematics and 12 papers in Molecular Biology. Recurrent topics in David L. Dowe's work include Computability, Logic, AI Algorithms (16 papers), Algorithms and Data Compression (12 papers) and Bayesian Methods and Mixture Models (10 papers). David L. Dowe is often cited by papers focused on Computability, Logic, AI Algorithms (16 papers), Algorithms and Data Compression (12 papers) and Bayesian Methods and Mixture Models (10 papers). David L. Dowe collaborates with scholars based in Australia, Spain and Germany. David L. Dowe's co-authors include José Hernández‐Orallo, Chris S. Wallace, Dean McKenzie, Sidney Bloch, David W. Kissane, Patrick Onghena, Christopher S. Wallace, Ben Ong, Susan Leekam and Lorna Wing and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Astrophysical Journal and NeuroImage.

In The Last Decade

David L. Dowe

69 papers receiving 1.1k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
David L. Dowe	471	232	208	208	147	78	1.2k
Keith Bush	298 0.6×	88 0.4×	346 1.7×	255 1.2×	63 0.4×	42	1.7k
Daniel S. Levine	460 1.0×	75 0.3×	817 3.9×	225 1.1×	134 0.9×	123	2.4k
Michael Jenkins	152 0.3×	74 0.3×	148 0.7×	246 1.2×	173 1.2×	84	1.6k
Steven Gregory	390 0.8×	99 0.4×	38 0.2×	127 0.6×	288 2.0×	89	1.7k
Joyce Shaffer	132 0.3×	113 0.5×	128 0.6×	36 0.2×	79 0.5×	10	1.6k
Ajit Narayanan	164 0.3×	103 0.4×	97 0.5×	50 0.2×	30 0.2×	98	939
Erik Linstead	368 0.8×	149 0.6×	502 2.4×	76 0.4×	28 0.2×	82	1.9k
Jukka-Pekka Onnela	229 0.5×	50 0.2×	758 3.6×	85 0.4×	178 1.2×	13	2.4k
Robert Matthews	411 0.9×	63 0.3×	28 0.1×	336 1.6×	52 0.4×	68	2.0k
Mathias Drton	732 1.6×	88 0.4×	198 1.0×	302 1.5×	46 0.3×	86	2.1k

Countries citing papers authored by David L. Dowe

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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20 of 20 papers shown

Peleg, Anton Y., Jiangning Song, Bhavna Antony, et al.. (2024). Predicting Pseudomonas aeruginosa drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra. mSystems. 9(9). e0078924–e0078924. 12 indexed citations

Dowe, David L., et al.. (2022). Trading Rule Search with Autoregressive Inference Agents. Figshare.

Makalic, Enes, Lloyd Allison, & David L. Dowe. (2022). MML Inference of Single-layer Neural Networks. Figshare. 636–642.

Fang, Zheng, David L. Dowe, Shelton Peiris, & Dedi Rosadi. (2021). Minimum Message Length in Hybrid ARMA and LSTM Model Forecasting. Entropy. 23(12). 1601–1601. 9 indexed citations

Casey, Andrew R., John C. Lattanzio, Aldeida Aleti, et al.. (2019). A Data-driven Model of Nucleosynthesis with Chemical Tagging in a Lower-dimensional Latent Space. The Astrophysical Journal. 887(1). 73–73. 9 indexed citations

Hernández‐Orallo, José, Fernando Martínez‐Plumed, Ute Schmid, Michael Siebers, & David L. Dowe. (2017). Computer models solving intelligence test problems: progress and implications. Monash University Research Portal (Monash University). 5005–5009.

Dowe, David L., et al.. (2016). Statistical compression-based models for text classification. FedUni ResearchOnline (Federation University Australia). 1–6. 2 indexed citations

Dowe, David L.. (2013). Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence: Papers from the Ray Solomonoff 85th Memorial Conference, ... / Lecture Notes in Artificial Intelligence. Springer eBooks. 1 indexed citations

Dowe, David L.. (2013). Algorithmic probability and friends : Bayesian prediction and artificial intelligence, papers from the Ray Solomonoff 85th memorial conference, Melbourne, VIC, Australia, November 30-December 2, 2011. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 3 indexed citations

10.

Dale, Pat, et al.. (2012). A novel approach for modeling malaria incidence using complex categorical household data: The minimum message length (MML) method applied to Indonesian data. SHILAP Revista de lepidopterología. 3 indexed citations

11.

Hernández‐Orallo, José, et al.. (2012). Turing machines and recursive Turing Tests. 28–33. 1 indexed citations

12.

Hernández‐Orallo, José, et al.. (2012). The ANYNT project intelligence test Λone. 20–27. 1 indexed citations

13.

Oppy, Graham & David L. Dowe. (2003). The Turing Test. 1–26. 21 indexed citations

14.

Dowe, David L., et al.. (2003). Unsupervised learning of Gamma mixture models using Minimum Message Length. 457–462. 10 indexed citations

15.

Dowe, David L., et al.. (2002). Univariate Polynomial Inference by Monte Carlo Message Length Approximation. International Conference on Machine Learning. 147–154. 8 indexed citations

16.

Dowe, David L., et al.. (2001). Message Length as an Effective Ockham’s Razor in Decision Tree Induction. International Conference on Artificial Intelligence and Statistics. 216–223. 19 indexed citations

17.

Powell, David, Lloyd Allison, Trevor I. Dix, & David L. Dowe. (1998). Alignment of Low Information Sequences.. 215–230. 4 indexed citations

18.

Dowe, David L. & Klaus Prank. (1997). Complexity and information-theoretic approaches to biology. 559–560. 1 indexed citations

19.

Dowe, David L., Kevin B. Korb, & Jonathan Oliver. (1996). Information, statistics and induction in science : proceedings of the conference, ISIS '96 : Melbourne, Australia, 20-23 August 1996. WORLD SCIENTIFIC eBooks.

20.

Baxter, Rohan A. & David L. Dowe. (1994). Model selection in linear regression using the MML criterion. 6 indexed citations

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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