Scott E. Decatur

547 citations
19 papers · 353 · h-index 11

Impact in

Papers in

Scott E. Decatur

17 papers receiving 332 citations

Peers

Scott E. Decatur
Comparison fields: 5 of 44
  • Artificial Intelligence 262
  • Computational Theory and Mathematics 85
  • Molecular Biology 112
  • Computer Graphics and Computer-Aided Design 5
  • Computer Networks and Communications 25
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Citations per year

Countries citing papers authored by Scott E. Decatur

Since Specialization
Citations

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

Fields of papers citing papers by Scott E. Decatur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott E. Decatur. 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 Scott E. Decatur. The network helps show where Scott E. Decatur may publish in the future.

Co-authors

The 16 scholars most cited alongside Scott E. Decatur, 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 Scott E. Decatur Line = papers co-authored together Scott E. Decatur links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 199765
2 199749
3 199640
4 199338
5 199534
6 199522
7 199818
8 199816
9
PAC Learning with Constant-Partition Classification Noise and Applications to Decision Tree Induction
199714
10 200014
11 199711
12 19967
13 19956
14
Efficient learning from faulty data
19956
15 20026
16 19974
17
Application of neural networks to terrain classification
19893
18 20200
19
A Probabilistic Error-Correcting Scheme.
19970

About Scott E. Decatur

Scott E. Decatur is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Condensed Matter Physics, Computer Networks and Communications and Materials Chemistry, having authored 19 papers that have together received 353 indexed citations. Recurring topics across this work include Algorithms and Data Compression (11 papers), Machine Learning and Algorithms (11 papers), Computability, Logic, AI Algorithms (4 papers), Protein Structure and Dynamics (3 papers), Enzyme Structure and Function (3 papers), Complexity and Algorithms in Graphs (3 papers), Theoretical and Computational Physics (2 papers) and Machine Learning and Data Classification (2 papers). The work is most often cited by research in Artificial Intelligence (262 citations), Computational Theory and Mathematics (85 citations), Molecular Biology (112 citations), Computer Graphics and Computer-Aided Design (5 citations) and Computer Networks and Communications (25 citations). Scott E. Decatur has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Javed A. Aslam, Javed Aslam, Vlado Dančík, Richa Agarwala, Sridhar Hannenhalli, Steven Skiena, Martı́n Farach-Colton, Serafim Batzoglou, S. Muthukrishnan and Rosario Gennaro. Their work appears in journals such as Journal of Computer and System Sciences, SIAM Journal on Computing, Journal of Computational Biology, Information and Computation and Information Processing Letters.

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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