Derek Partridge

1.6k citations
71 papers · 799 indexed · h-index 16
Topics
Neural Networks and Applications (9 papers)Computability, Logic, AI Algorithms (9 papers)Software Engineering Research (7 papers)

In The Last Decade

Derek Partridge

68 papers receiving 692 citations

Peers

Derek Partridge
Comparison fields: 5 of 129
  • Artificial Intelligence 435
  • Information Systems 118
  • Computational Theory and Mathematics 89
  • Computer Vision and Pattern Recognition 86
  • Cognitive Neuroscience 69
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Countries citing papers authored by Derek Partridge

Since Specialization
Citations

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

Fields of papers citing papers by Derek Partridge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Derek Partridge. 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 Derek Partridge. The network helps show where Derek Partridge may publish in the future.

Co-authorship network of co-authors of Derek Partridge

This figure shows the co-authorship network connecting the top 25 collaborators of Derek Partridge. A scholar is included among the top collaborators of Derek Partridge 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 Derek Partridge. Derek Partridge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 6
2 42
3 19
4 8
5
Self-Organizing Decomposition of Functions in the Context of a Unified Framework for Multiple Classifier Systems
1
6 7
7
Multi-Version Systems of Neural Networks for Predicting the Risk of Osteoporosis
1
8 6
9
Replicability of Neural Computing Experiments.
4
10
Neural computing: a new route to software reliability
2
11
A biologically based algorithm for rapid scene analysis
1
12
AI programs and cognitive models: models of perceptual processes
2
13 3
14
Surprisingness and expectation failure: what's the difference?
48
15
Will AI lead to a super software crisis
2
16
Attentional Algorithms for Rapid Scene Analysis
1
17
Artificial intelligence and business management
3
18
Input-expectation discrepancy reduction: a ubiquitous mechanism
5
19
A philosophy of 'wicked' problem implementation
1
20 3

About Derek Partridge

Derek Partridge is a scholar working on Software, History and Philosophy of Science and Artificial Intelligence, having authored 71 papers that have together received 799 indexed citations. Recurring topics across this work include Neural Networks and Applications (9 papers), Computability, Logic, AI Algorithms (9 papers) and Software Engineering Research (7 papers). The work is most often cited by research in Artificial Intelligence (435 citations), Software (43 citations) and Health Informatics (14 citations). Derek Partridge has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include W. J. Krzanowski, Andrew Ortony, Yorick Wilks, Vitaly Schetinin, Trevor Bailey, Richard Everson, Jonathan E. Fieldsend, Niall Griffith, Shuang Cang and Victor S. Johnston. Their work appears in journals such as Communications of the ACM, Journal of Theoretical Biology and Computer.

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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