On a 3-class MNIST subset, a competitive-Hebbian + weight-perturbation rule achieves higher estimated mutual information per nonsilent synapse than BP, but with much lower accuracy and no error bars.
Communication in neuronal networks,
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Energy-Efficient Information Representation in MNIST Classification Using Biologically Inspired Learning
On a 3-class MNIST subset, a competitive-Hebbian + weight-perturbation rule achieves higher estimated mutual information per nonsilent synapse than BP, but with much lower accuracy and no error bars.