Contrastive Hebbian learning is a biologically plausible form of Hebbian learning.
It is based on the contrastive divergence algorithm, which has been used to train a variety of energy-based latent variable models.
[1] In 2003, contrastive Hebbian learning was shown to be equivalent in power to the backpropagation algorithms commonly used in machine learning.
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