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- Q17145678 subject Q6193293.
- Q17145678 subject Q8921727.
- Q17145678 abstract "Maximally informative dimensions is a dimensionality reduction technique used in the statistical analyses of neural responses. Specifically, it is a way of projecting a stimulus onto a low-dimensional subspace so that as much information as possible about the stimulus is preserved in the neural response. It is motivated by the fact that natural stimuli are typically confined by their statistics to a lower-dimensional space than that spanned by white noise. Within this subspace, however, stimulus-response functions may be either linear or nonlinear. The idea was originally developed by Tatyana Sharpee, Nicole Rust, and William Bialek in 2003.".
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- Q17145678 wikiPageWikiLink Q16000077.
- Q17145678 wikiPageWikiLink Q1753188.
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- Q17145678 wikiPageWikiLink Q252973.
- Q17145678 wikiPageWikiLink Q2796622.
- Q17145678 wikiPageWikiLink Q381287.
- Q17145678 wikiPageWikiLink Q415072.
- Q17145678 wikiPageWikiLink Q43054.
- Q17145678 wikiPageWikiLink Q448916.
- Q17145678 wikiPageWikiLink Q6193293.
- Q17145678 wikiPageWikiLink Q660848.
- Q17145678 wikiPageWikiLink Q7002051.
- Q17145678 wikiPageWikiLink Q7577161.
- Q17145678 wikiPageWikiLink Q8005525.
- Q17145678 wikiPageWikiLink Q8921727.
- Q17145678 comment "Maximally informative dimensions is a dimensionality reduction technique used in the statistical analyses of neural responses. Specifically, it is a way of projecting a stimulus onto a low-dimensional subspace so that as much information as possible about the stimulus is preserved in the neural response. It is motivated by the fact that natural stimuli are typically confined by their statistics to a lower-dimensional space than that spanned by white noise.".
- Q17145678 label "Maximally informative dimensions".