Pages that link to "Item:Q4814195"
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The following pages link to Learning the Nonlinearity of Neurons from Natural Visual Stimuli (Q4814195):
Displaying 11 items.
- Energy levels of Moiré patterns: relation to human perception (Q2373150) (← links)
- Learning viewpoint invariant object representations using a temporal coherence principle (Q2576477) (← links)
- Multinomial Bayesian learning for modeling classical and nonclassical receptive field properties (Q2919433) (← links)
- Psychophysically Tuned Divisive Normalization Approximately Factorizes the PDF of Natural Images (Q3067077) (← links)
- Active Data Collection for Efficient Estimation and Comparison of Nonlinear Neural Models (Q3116928) (← links)
- A Maximum-Likelihood Interpretation for Slow Feature Analysis (Q3440426) (← links)
- Closed-Form Expressions of Some Stochastic Adapting Equations for Nonlinear Adaptive Activation Function Neurons (Q4819862) (← links)
- Competitive learning, natural images and cortical cells (Q4855359) (← links)
- Learning in the context of nonlinear psychophysics: The Gamma Zak Embedding (Q5287157) (← links)
- Learning Visual Spatial Pooling by Strong PCA Dimension Reduction (Q5380541) (← links)
- A Simple Hebbian/Anti-Hebbian Network Learns the Sparse, Independent Components of Natural Images (Q5473191) (← links)
