Difference between revisions of "Neural computational models"
From Eyewire
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− | == Hebbian (self-organizing, associative) models == | + | <translate> |
+ | |||
+ | == Hebbian (self-organizing, unsupervised, associative) models == | ||
* [[Hebb's rule]] | * [[Hebb's rule]] | ||
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* [[Sanger's rule]] | * [[Sanger's rule]] | ||
* [[Conditional principal components analysis]] | * [[Conditional principal components analysis]] | ||
+ | * [[Autoencoder]] | ||
+ | * [[Restricted Boltzmann machine]] | ||
− | == Error-driven models == | + | == Error-driven models (supervised) == |
* [[Feedforward backpropagation]] | * [[Feedforward backpropagation]] | ||
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* see [ftp://grey.colorado.edu/pub/oreilly/thesis/oreilly_thesis.all.pdf The LEABRA Model of Neural Interactions and Learning in the Neocortex] | * see [ftp://grey.colorado.edu/pub/oreilly/thesis/oreilly_thesis.all.pdf The LEABRA Model of Neural Interactions and Learning in the Neocortex] | ||
+ | |||
+ | </translate> |
Latest revision as of 03:20, 24 June 2016
Hebbian (self-organizing, unsupervised, associative) models
- Hebb's rule
- Oja's rule
- Sanger's rule
- Conditional principal components analysis
- Autoencoder
- Restricted Boltzmann machine