The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Approximation by superpositions of a sigmoidal function
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Citations
Cites
Approximation by superpositions of a sigmoidal function
Cybenko, G. (1989) · Mathematics of Control, Signals, and Systems · doi:10.1007/bf02551274 · Cited by 13,883
Self-citation
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“According to the universal approximation theorem [5, 16], under certain conditions, neural networks are universal approximators of continuous functions over compact sets.”
BackgroundOptimization problems for machine learning: A survey
Gambella, C., Ghaddar, B., & Naoum-Sawaya, J. (2021) · European Journal of Operational Research · doi:10.1016/j.ejor.2020.08.045 · Cited by 365
LIMITATIONS OF PHYSICS INFORMED MACHINE LEARNING FOR NONLINEAR TWO-PHASE TRANSPORT IN POROUS MEDIA
Fuks, O., & Tchelepi, H. A. (2020) · Journal of Machine Learning for Modeling and Computing · doi:10.1615/jmachlearnmodelcomput.2020033905 · Cited by 303
Learning Optimal Resource Allocations in Wireless Systems
Eisen, M., Zhang, C., Chamon, L. F. O., Lee, D. D., & Ribeiro, A. (2019) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2019.2908906 · Cited by 253
Metadata
- Authors
- Cybenko, G.
- Venue
- Mathematics of Control, Signals, and Systems
- Published
- 1992-12
- Volume
- 5
- Issue
- 4
- Pages
- 455-455
- ISSN
- 0932-4194 (ISSN-L)
- 1435-568X
- OpenAlex
- W4242989628
- Cited by
- 703
- References
- 1
- FWCI
- 2.24
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.
