Mark Derthick

456 citations
24 papers · 261 · h-index 10

Impact in

Papers in

Mark Derthick

22 papers receiving 234 citations

Peers

Mark Derthick
Comparison fields: 5 of 49
  • Computer Vision and Pattern Recognition 149
  • Signal Processing 52
  • Information Systems and Management 30
  • Artificial Intelligence 97
  • Human-Computer Interaction 12
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Citations per field
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Citations per year

Countries citing papers authored by Mark Derthick

Since Specialization
Citations

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

Fields of papers citing papers by Mark Derthick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Mark Derthick, 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 Mark Derthick Line = papers co-authored together Mark Derthick links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199757
2 200137
3
Mundane reasoning by parallel constraint satisfaction
199025
4 200019
5
Is Distributed Connectionism Compatible with the Physical Symbol System Hypothesis
198616
6 200414
7 199013
8 200311
9
A minimal encoding approach to feature discovery
19919
10
Variations on the Boltzmann Machine Learning Algorithm
19849
11 20029
12 20018
13
Counterfactual reasoning with direct models
19876
14 20025
15 20185
16 19905
17 20083
18 20183
19
Ensemble' Boltzmann Units have Collective Computational Properties like those of Hopfield and Tank Neurons
19872
20 20012

About Mark Derthick

Mark Derthick is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Signal Processing and Computational Theory and Mathematics, having authored 24 papers that have together received 261 indexed citations. Recurring topics across this work include Data Visualization and Analytics (9 papers), Advanced Database Systems and Queries (6 papers), Data Management and Algorithms (6 papers), Neural Networks and Applications (4 papers), Video Analysis and Summarization (4 papers), Image Retrieval and Classification Techniques (3 papers), AI-based Problem Solving and Planning (2 papers) and Bayesian Modeling and Causal Inference (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (149 citations), Signal Processing (52 citations), Information Systems and Management (30 citations), Artificial Intelligence (97 citations) and Human-Computer Interaction (12 citations). Mark Derthick has collaborated with scholars based in United States and France. Frequent co-authors include Steven F. Roth, John Kolojejchick, Geoffrey E. Hinton, David C. Plaut, Howard D. Wactlar, Michael G. Christel, Alexander G. Hauptmann, Andrew W. Moore, John Zimmerman and Weihao Lin. Their work appears in journals such as Artificial Intelligence, Bioinformatics, Knowledge-Based Systems, Medical Entomology and Zoology and National Conference on Artificial Intelligence.

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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