The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Mapping part-whole hierarchies into connectionist networks
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Citations
Cites
Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986) · Nature · doi:10.1038/323533a0 · Cited by 31,892
Self-citationNeural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
McClelland, J. L., & Rumelhart, D. E. (1981) · Psychological Review · doi:10.1037/0033-295x.88.5.375 · Cited by 4,889
Some Studies in Machine Learning Using the Game of Checkers
Samuel, A. L. (1959) · IBM Journal of Research and Development · doi:10.1147/rd.33.0210 · Cited by 4,443
Connectionism and cognitive architecture: A critical analysis
Fodor, J. A., & Pylyshyn, Z. W. (1988) · Cognition · doi:10.1016/0010-0277(88)90031-5 · Cited by 4,022
On the proper treatment of connectionism
Smolensky, P. (1988) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00052432 · Cited by 2,085
Single Units and Sensation: A Neuron Doctrine for Perceptual Psychology?
Barlow, H. B. (1972) · Perception · doi:10.1068/p010371 · Cited by 1,730
Hillis, W. D. (1987) · Scientific American · doi:10.1038/scientificamerican0687-108 · Cited by 1,635
Parallel models of associative memory
Heath, R. (1982) · Journal of Mathematical Psychology · doi:10.1016/0022-2496(82)90036-0 · Cited by 1,095
Hinton, G. E. (2018) · KiltHub Repository · doi:10.1184/r1/6604925 · Cited by 1,025
Self-citation
Cited by
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
Socher, R., Perelygin, A., Wu, J., Chuang, J., Manning, C. D., Ng, A., & Potts, C. (2013) · Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d13-1170 · Cited by 6,878
Deep Learning: Methods and Applications
Deng, L., & Yu, D. (2014) · Foundations and Trends® in Signal Processing · doi:10.1561/2000000039 · Cited by 3,480
Representativeness revisited: Attribute substitution in intuitive judgment.
Kahneman, D., & Frederick, S. (2002) · Heuristics and Biases · doi:10.1017/cbo9780511808098.004 · Cited by 3,476
Understanding normal and impaired word reading: Computational principles in quasi-regular domains.
Plaut, D. C., McClelland, J. L., Seidenberg, M. S., & Patterson, K. (1996) · Psychological Review · doi:10.1037/0033-295x.103.1.56 · Cited by 2,698
Slovic, P., Finucane, M., Peters, E., & MacGregor, D. G. (2002) · Heuristics and Biases · doi:10.1017/cbo9780511808098.025 · Cited by 2,349
Metadata
- Authors
- Hinton, G. E.
- Venue
- Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 1990-11
- Volume
- 46
- Issue
- 1-2
- Pages
- 47-75
- ISSN
- 0004-3702 (ISSN-L)
- OpenAlex
- W2110377720
- Cited by
- 310
- References
- 34
- FWCI
- 9.50
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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- CoChat. (2026). Citation check: Mapping part-whole hierarchies into connectionist networks. https://app.cochat.ai/papers/10.1016/0004-3702(90)90004-j
- The paper
- Hinton, G. E. (1990). Mapping part-whole hierarchies into connectionist networks. Artificial Intelligence. https://doi.org/10.1016/0004-3702(90)90004-j
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
