Second order dimensionality reduction using minimum and maximum mutual information models
about
Information theoretic approaches to understanding circuit functionReceptive Field Vectors of Genetically-Identified Retinal Ganglion Cells Reveal Cell-Type-Dependent Visual FunctionsModels of Neuronal Stimulus-Response Functions: Elaboration, Estimation, and Evaluation.How Invariant Feature Selectivity Is Achieved in CortexDynamic Reweighting of Auditory Modulation Filters.Central auditory neurons have composite receptive fields.Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the RetinaTemporal variability of spectro-temporal receptive fields in the anesthetized auditory cortexDiscriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles.Maximally informative "stimulus energies" in the analysis of neural responses to natural signals.Understanding spike-triggered covariance using Wiener theory for receptive field identification.Cross-orientation suppression in visual area V2Construction of direction selectivity through local energy computations in primary visual cortex.Inferring nonlinear neuronal computation based on physiologically plausible inputsSpike triggered covariance in strongly correlated gaussian stimuli.Beyond GLMs: a generative mixture modeling approach to neural system identification.Neural Mechanisms for Evaluating Environmental Variability in Caenorhabditis elegansIdentifying functional bases for multidimensional neural computations.Computational identification of receptive fields.Learning quadratic receptive fields from neural responses to natural stimuli.Multidimensional receptive field processing by cat primary auditory cortical neurons.Analysis of Neuronal Spike Trains, Deconstructed.Dimensionality reduction in neuroscience.The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction.A Low-Rank Method for Characterizing High-Level Neural Computations.Capturing the Dynamical Repertoire of Single Neurons with Generalized Linear Models.Understanding Neural Population Coding: Information Theoretic Insights from the Auditory System
P2860
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P2860
Second order dimensionality reduction using minimum and maximum mutual information models
description
2011 nî lūn-bûn
@nan
2011 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年学术文章
@wuu
2011年学术文章
@zh-cn
2011年学术文章
@zh-hans
2011年学术文章
@zh-my
2011年学术文章
@zh-sg
2011年學術文章
@yue
name
Second order dimensionality reduction using minimum and maximum mutual information models
@ast
Second order dimensionality reduction using minimum and maximum mutual information models
@en
Second order dimensionality reduction using minimum and maximum mutual information models
@nl
type
label
Second order dimensionality reduction using minimum and maximum mutual information models
@ast
Second order dimensionality reduction using minimum and maximum mutual information models
@en
Second order dimensionality reduction using minimum and maximum mutual information models
@nl
prefLabel
Second order dimensionality reduction using minimum and maximum mutual information models
@ast
Second order dimensionality reduction using minimum and maximum mutual information models
@en
Second order dimensionality reduction using minimum and maximum mutual information models
@nl
P2093
P2860
P1476
Second order dimensionality reduction using minimum and maximum mutual information models
@en
P2093
Jeffrey D Fitzgerald
Lawrence C Sincich
Ryan J Rowekamp
Tatyana O Sharpee
P2860
P304
P356
10.1371/JOURNAL.PCBI.1002249
P577
2011-10-27T00:00:00Z