The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Outlier Detection Using Replicator Neural Networks
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Citations
Cites
(1996) · Cited by 20,179
LOF: identifying density-based local outliers
Breunig, M. M., Kriegel, H.-P., Ng, R. T., & Sander, J. (2000) · ACM SIGMOD Record · doi:10.1145/335191.335388 · Cited by 5,207
LOF: identifying density-based local outliers
Breunig, M. M., Kriegel, H.-P., Ng, R. T., & Sander, J. (2000) · Proceedings of the 2000 ACM SIGMOD international conference on Management of data · doi:10.1145/342009.335388 · Cited by 4,149
BIRCH: an efficient data clustering method for very large databases
Zhang, T., Ramakrishnan, R., & Livny, M. (1996) · Proceedings of the 1996 ACM SIGMOD international conference on Management of data - SIGMOD '96 · doi:10.1145/233269.233324 · Cited by 3,935
A learning algorithm for Boltzmann machines
Ackley, D. H., Hinton, G. E., & Sejnowski, T. J. (1985) · Cognitive Science · doi:10.1207/s15516709cog0901_7 · Cited by 3,402
Hawkins, D. M. (1980) · doi:10.1007/978-94-015-3994-4 · Cited by 2,982
BIRCH: an efficient data clustering method for very large databases
Zhang, T., Ramakrishnan, R., & Livny, M. (1996) · ACM SIGMOD Record · doi:10.1145/235968.233324 · Cited by 2,097
Efficient algorithms for mining outliers from large data sets
Ramaswamy, S., Rastogi, R., & Shim, K. (2000) · ACM SIGMOD Record · doi:10.1145/335191.335437 · Cited by 1,860
Efficient and Effective Clustering Methods for Spatial Data Mining
Ng, R. T., & Han, J. (1994) · Cited by 1,778
Algorithms for Mining Distance-Based Outliers in Large Datasets
Knorr, E. M., & Ng, R. T. (1998) · Cited by 1,544
Cited by
Chandola, V., Banerjee, A., & Kumar, V. (2009) · ACM Computing Surveys · doi:10.1145/1541880.1541882 · Cited by 11,687
Deep Learning for Anomaly Detection: A Review
Pang, G., Shen, C., Cao, L., & Hengel, A. V. D. (2022) · ACM Computing Surveys · doi:10.1145/3439950 · Cited by 2,837
Pimentel, M. A. F., Clifton, D. A., Clifton, L., & Tarassenko, L. (2014) · Signal Processing · doi:10.1016/j.sigpro.2013.12.026 · Cited by 1,649
Anomaly Detection Using Autoencoders with Nonlinear Dimensionality Reduction
Sakurada, M., & Yairi, T. (2014) · Proceedings of the MLSDA 2014 2nd Workshop on Machine Learning for Sensory Data Analysis · doi:10.1145/2689746.2689747 · Cited by 1,438
Deep Learning for Anomaly Detection: A Survey
Chalapathy, R., & Chawla, S. (2019) · arXiv · doi:10.48550/arxiv.1901.03407 · Cited by 1,240
Metadata
- Authors
- Hawkins, S., He, H., Williams, G., & Baxter, R.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2002
- Pages
- 170-180
- ISSN
- 0302-9743 (ISSN-L)
- OpenAlex
- W1876967670
- Cited by
- 710
- References
- 22
- FWCI
- 4.35
- Type
- conference paper
- 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.
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- CoChat. (2026). Citation check: Outlier Detection Using Replicator Neural Networks. https://app.cochat.ai/papers/10.1007/3-540-46145-0_17
- The paper
- Hawkins, S., He, H., Williams, G., & Baxter, R. (2002). Outlier Detection Using Replicator Neural Networks. Lecture Notes in Computer Science. https://doi.org/10.1007/3-540-46145-0_17
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.
