The DOI matches its OpenAlex record; 1 of the 1 references it cites were found in a registry or an index.
Learning Multiple Layers of Features from Tiny Images
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Citations
Cites
WordNet: a lexical database for English
Miller, G. A. (1995) · Communications of the ACM · doi:10.1145/219717.219748 · Cited by 14,015
Cited by
Items 601–606 of 606
Sanity Checks for Saliency Metrics
Tomsett, R., Harborne, D., Chakraborty, S., Gurram, P., & Preece, A. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i04.6064 · Cited by 3
Joint Client Scheduling and Resource Allocation Under Channel Uncertainty in Federated Learning
Wadu, M. M., Samarakoon, S., & Bennis, M. (2021) · IEEE Transactions on Communications · doi:10.1109/tcomm.2021.3088528 · Cited by 2
Uncertainty Quantification in Deep Residual Neural Networks
Wandzik, L., Garcia, R. V., & Krüger, J. (2020) · arXiv · doi:10.48550/arxiv.2007.04905 · Cited by 1
Image Compression: Sparse Coding vs. Bottleneck Autoencoders
Watkins, Y., Iaroshenko, O., Sayeh, M., & Kenyon, G. (2018) · 2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) · doi:10.1109/ssiai.2018.8470336
Constructing Fast Network through Deconstruction of Convolution
Jeon, Y., & Kim, J. (2018) · arXiv · doi:10.48550/arxiv.1806.07370
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
Hendrycks, D., Mu, N., Cubuk, E. D., Zoph, B., Gilmer, J., & Lakshminarayanan, B. (2019) · arXiv · doi:10.48550/arxiv.1912.02781
Metadata
- Authors
- Krizhevsky, A.
- Published
- 2024-01-01
- OpenAlex
- W3118608800
- Cited by
- 23,395
- References
- 1
- FWCI
- 559.79
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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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.
