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Estimating mutual information
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“The information-theoretic neuroscience literature has long recognized the importance of correcting for the limited-sampling bias and has provided effective tools for correcting the Shannon information sampling bias.24,25,26,27,28”
From Sampling bias corrections for discrete and Gaussian partial information decompositions (2026) · cites this paper as [28]
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Research works printed but not linked: 36
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Metadata
- Authors
- Kraskov, A., Stögbauer, H., & Grassberger, P.
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 2004-06-23
- Volume
- 69
- Issue
- 6
- ISSN
- 1539-3755
- 1550-2376
- Cited by
- 3,512
- References
- 0
- Language
- en
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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: Estimating mutual information. https://app.cochat.ai/papers/10.1103/physreve.69.066138
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- Kraskov, A., Stögbauer, H., & Grassberger, P. (2004). Estimating mutual information. Physical Review E. https://doi.org/10.1103/physreve.69.066138