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David E. Rumelhart

Affiliations: 
Stanford University, Palo Alto, CA 
Area:
Neural nets
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"David Rumelhart"
Bio:

David Rumelhart has made many contributions to the formal analysis of human cognition, working primarily within the frameworks of mathematical psychology, symbolic artificial intelligence, and parallel distributed processing. He also admired formal linguistic approaches to cognition and explored the possibility of formulating a formal grammar to capture the structure of stories. In 1986, he published Parallel distributed processing: Explorations in the microstructure of cognition with James McClelland, which some still regard as a bible for cognitive scientists. (From Wikipedia) d. 3/13/11

Cross-listing: Neurotree - MathTree

Parents

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William K. Estes grad student 1967 Stanford (Neurotree)

Children

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Yuko Munakata research assistant 1990-1991 Stanford (Neurotree)
Stephen A. Engel grad student Stanford (Neurotree)
Dedre Gentner grad student UCSD (Neurotree)
Raymond W. Gibbs grad student UCSD (Neurotree)
Kenneth J Kurtz grad student Stanford (Neurotree)
Stephen E. Palmer grad student 1970-1974 UCSD
Robert J. Glushko grad student 1979 UCSD (Computer Science Tree)
Arthur Gary Samuel grad student 1979 University of California, San Diego ; Columbia University (Neurotree)
Michael I. Jordan grad student 1985 UCSD (Neurotree)
Peter Martin Todd grad student 1992 Stanford (Neurotree)
Garrison Cottrell post-doc UCSD (Neurotree)
Richard Golden post-doc Stanford (Neurotree)
Colleen Seifert post-doc UCSD
Philip Servos post-doc 1994-1996 Stanford (Neurotree)

Collaborators

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Don Norman collaborator UCSD (Neurotree)
James L. McClelland collaborator 1976-1984 UCSD (Neurotree)
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Publications

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McClelland JL, Rumelhart DE. (2013) An Interactive Activation Model of Context Effects in Letter Perception: Part I. An Account of Basic Findings Readings in Cognitive Science: a Perspective From Psychology and Artificial Intelligence. 580-596
Rumelhart DE, Smolensky P, McClelland JL, et al. (2013) Schemata and Sequential Thought Processes in PDP Models Readings in Cognitive Science: a Perspective From Psychology and Artificial Intelligence. 224-249
McClelland JL, Rumelhart DE, Hinton GE. (2013) The Appeal of Parallel Distributed Processing Readings in Cognitive Science: a Perspective From Psychology and Artificial Intelligence. 52-72
Servos P, Zacks J, Rumelhart DE, et al. (1998) Somatotopy of the human arm using fMRI. Neuroreport. 9: 605-9
Engel SA, Rumelhart DE, Wandell BA, et al. (1994) fMRI of human visual cortex. Nature. 369: 525
Franco H, Cohen M, Morgan N, et al. (1994) Context-dependent connectionist probability estimation in a hybrid hidden Markov model-neural net speech recognition system Computer Speech and Language. 8: 211-222
Golden RM, Rumelhart DE. (1993) A Parallel Distributed Processing Model of Story Comprehension and Recall Discourse Processes. 16: 203-237
Jordan MI, Rumelhart DE. (1992) Forward models: Supervised learning with a distal teacher Cognitive Science. 16: 307-354
Kawamoto AH, McClelland JL, Rumelhart DE. (1989) Explorations in Parallel Distributed Processing: A Handbook of Models, Programs, and Exercises The American Journal of Psychology. 102: 435
McClelland JL, Rumelhart DE. (1988) A simulation-based tutorial system for exploring parallel distributed processing Behavior Research Methods, Instruments, & Computers. 20: 263-275
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