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David E. Rumelhart

David E. Rumelhart

D-Index & Metrics

Engineering and Technology

D-Index
66
Citations
163768
World Ranking
1355
National Ranking
440

Research.com Recognitions

  • 2002 - Grawemeyer Award in Psychology, University of Louisville
  • 2001 - Neural Networks Pioneer Award, IEEE Computational Intelligence Society
  • 1996 - APA Award for Distinguished Scientific Contributions to Psychology, American Psychological Association
  • 1991 - Member of the National Academy of Sciences
  • 1990 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 1990 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI)
  • 1987 - Fellow of the MacArthur Foundation

Overview

David E. Rumelhart was associated with Stanford University in the United States. Throughout their career, they contributed to the academic community notably in collaboration with frequent co-author James L. McClelland.

Rumelhart received multiple recognitions acknowledging various aspects of their contributions to psychology and cognitive science. The awards included:

  • Grawemeyer Award in Psychology, University of Louisville (2002)
  • Neural Networks Pioneer Award, IEEE Computational Intelligence Society (2001)
  • APA Award for Distinguished Scientific Contributions to Psychology, American Psychological Association (1996)
  • Member of the National Academy of Sciences (1991)
  • Fellow of the American Association for the Advancement of Science (AAAS) (1990)
  • Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) (1990)
  • Fellow of the MacArthur Foundation (1987)

While there are no records of recent papers, book publications, or specific fields and subfields of study listed, the collaborations and awards suggest significant involvement in neural networks, psychology, and artificial intelligence research domains.

Best Publications

  • Learning representations by back-propagating errors

    David E. Rumelhart;Geoffrey E. Hinton;Ronald J. Williams

  • Learning internal representations by error propagation

    D. E. Rumelhart;G. E. Hinton;R. J. Williams

  • Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations

    David E. Rumelhart;James L. McClelland;Au

  • Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations

    David E. Rumelhart;James L. McClelland

  • On learning the past tenses of English verbs

    David E. Rumelhart;James L. McClelland

  • Forward models: supervised learning with a distal teacher

    Michael I. Jordan;David E. Rumelhart

  • Distributed representations

    G. E. Hinton;J. L. McClelland;D. E. Rumelhart

  • NOTES ON A SCHEMA FOR STORIES

    David E. Rumelhart

  • Feature discovery by competitive learning

    David E. Rumelhart;David Zipser

  • A general framework for parallel distributed processing

    D. E. Rumelhart;G. E. Hinton;J. L. McClelland

  • Schemata and sequential thought processes in PDP models

    D. E. Rumelhart;P. Smolensky;J. L. McClelland;G. E. Hinton

  • Distributed memory and the representation of general and specific information.

    James L. McClelland;David E. Rumelhart

  • Explorations in cognition

    Donald A. Norman;David E. Rumelhart

  • The appeal of parallel distributed processing

    J. L. McClelland;D. E. Rumelhart;G. E. Hinton

  • fMRI of human visual cortex

    Stephen A. Engel;David E. Rumelhart;Brian A. Wandell;Adrian T. Lee

  • Parallel distributed processing: explorations in the microstructure of cognition, vol. 2: psychological and biological models

    David E. Rumelhart;James L. McClelland

  • PREDICTING THE FUTURE: A CONNECTIONIST APPROACH

    Andreas S. Weigend;Bernardo A. Huberman;David E. Rumelhart

  • On learning the past-tenses of English verbs: implicit rules or parallel distributed processing

    Unknown

  • Generalization by Weight-Elimination with Application to Forecasting

    Andreas S. Weigend;David E. Rumelhart;Bernardo A. Huberman

  • Explorations in parallel distributed processing: a handbook of models, programs, and exercises

    James L. McClelland;David E. Rumelhart

  • Neural networks: applications in industry, business and science

    Bernard Widrow;David E. Rumelhart;Michael A. Lehr

  • Parallel Distributed Processing: Explorations in the Microstructures of Cognition

    Geoffrey Sampson;David E. Rumelhart;James L. McClelland

  • An interactive activation model of context effects in letter perception: part 1.: an account of basic findings

    James L. McClelland;David E. Rumelhart

Frequent Co-Authors

James L. McClelland
James L. McClelland Stanford University
Donald A. Norman
Donald A. Norman University of California, San Diego
Geoffrey E. Hinton
Geoffrey E. Hinton University of Toronto
Nelson Morgan
Nelson Morgan International Computer Science Institute
Horacio Franco
Horacio Franco SRI International
Michael I. Jordan
Michael I. Jordan University of California, Berkeley
Gary H. Glover
Gary H. Glover Stanford University
Andrew Ortony
Andrew Ortony Northwestern University
Bernard Widrow
Bernard Widrow Stanford University

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