David C. Noelle

1.6k total citations
48 papers, 888 citations indexed

About

David C. Noelle is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Developmental and Educational Psychology. According to data from OpenAlex, David C. Noelle has authored 48 papers receiving a total of 888 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Cognitive Neuroscience, 14 papers in Artificial Intelligence and 9 papers in Developmental and Educational Psychology. Recurrent topics in David C. Noelle's work include Neural dynamics and brain function (15 papers), Memory and Neural Mechanisms (8 papers) and Neural and Behavioral Psychology Studies (7 papers). David C. Noelle is often cited by papers focused on Neural dynamics and brain function (15 papers), Memory and Neural Mechanisms (8 papers) and Neural and Behavioral Psychology Studies (7 papers). David C. Noelle collaborates with scholars based in United States, India and Germany. David C. Noelle's co-authors include Jonathan D. Cohen, Randall C. O’Reilly, Todd S. Braver, Linda B. Smith, Mark S. Seidenberg, Timothy T. Rogers, James L. McClelland, David C. Plaut, Matthew Botvinick and Joshua L. Phillips and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

David C. Noelle

45 papers receiving 838 citations

Peers

David C. Noelle
Comparison fields: 5 of 92
  • Cognitive Neuroscience 539
  • Artificial Intelligence 235
  • Developmental and Educational Psychology 197
  • Social Psychology 113
  • Experimental and Cognitive Psychology 107
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Citations per field, relative to David C. Noelle
David C. Noelle · 1×
Citations per year, relative to David C. Noelle
David C. Noelle · 1×

Countries citing papers authored by David C. Noelle

Since Specialization
Citations

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

Fields of papers citing papers by David C. Noelle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David C. Noelle. 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 C. Noelle. The network helps show where David C. Noelle may publish in the future.

Co-authorship network of co-authors of David C. Noelle

This figure shows the co-authorship network connecting the top 25 collaborators of David C. Noelle. A scholar is included among the top collaborators of David C. Noelle 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 C. Noelle. David C. Noelle 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
# Work Indexed citations
1 6
2
Lateral Inhibition Overcomes Limits of Temporal Difference Learning.
2
3
Robotic Learning Of The Delayed Saccade Task Using A Neurally Inspired Adaptive Working Memory System.
1
4
Using Case-Based Reasoning to Improve the Quality of Feedback Provided by Automated Grading Systems
2
5
Implications of Polychronous Neuronal Groups for the Nature of Mental Representations
3
6 236
7
Implicit Learning Deficits in Autism: A Neurocomputational Account
2
8
Impaired Cognitive Flexibility & Stimulus Overselectivity in Autism
1
9
A dual-pathway neural network model of control relinquishment in motor skill learning
3
10
Collaboratory: An Open Source Teaching and Learning Facility for Computer Science and Engineering Education
6
11
A computational neuroscience model of working memory with application to robot perceptual learning
6
12
Lateral Inhibition Explains Savings in Conditioning and Extinction
0
13
Neurocomputational Mechanisms for Generalization During the Sequential Learning of Multiple Tasks.
2
14
The Role of Neurocomputational Principles in Skill Savings
4
15
The Universal Theory Model of Concepts and the Dissolution of the Puzzle of Concept Acquisition
2
16
Reinforcement Learning of Dimensional Attention for Categorization
5
17
A Biologically Inspired Adaptive Working Memory for Robots.
19
18
Individual Differences in Exemplar-Based Interference During Instructed Category Learning
5
19
In Search Of Articulated Attractors
1
20
A connectionist model of instructed learning
8

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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