Difference between revisions of "Neural computational models"
From Eyewire
(Created page with "* Hebb's rule * Oja's rule * Sanger's rule") |
|||
(9 intermediate revisions by 2 users not shown) | |||
Line 1: | Line 1: | ||
+ | <translate> | ||
+ | |||
+ | == Hebbian (self-organizing, unsupervised, associative) models == | ||
+ | |||
* [[Hebb's rule]] | * [[Hebb's rule]] | ||
* [[Oja's rule]] | * [[Oja's rule]] | ||
* [[Sanger's rule]] | * [[Sanger's rule]] | ||
+ | * [[Conditional principal components analysis]] | ||
+ | * [[Autoencoder]] | ||
+ | * [[Restricted Boltzmann machine]] | ||
+ | |||
+ | == Error-driven models (supervised) == | ||
+ | |||
+ | * [[Feedforward backpropagation]] | ||
+ | * [[Almeida-Pineda recurrent backpropagation]] | ||
+ | * [[Contrastive Hebbian learning]] | ||
+ | |||
+ | == LEABRA == | ||
+ | |||
+ | * 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