A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks
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Spontaneous emergence of fast attractor dynamics in a model of developing primary visual cortex.Robust Exponential Memory in Hopfield Networks.Is cortical connectivity optimized for storing information?Effect of similarity between patterns in associative memory.From statistical inference to a differential learning rule for stochastic neural networks
P2860
A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks
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name
A Three-Threshold Learning Rul ...... y of Recurrent Neural Networks
@ast
A Three-Threshold Learning Rul ...... y of Recurrent Neural Networks
@en
type
label
A Three-Threshold Learning Rul ...... y of Recurrent Neural Networks
@ast
A Three-Threshold Learning Rul ...... y of Recurrent Neural Networks
@en
prefLabel
A Three-Threshold Learning Rul ...... y of Recurrent Neural Networks
@ast
A Three-Threshold Learning Rul ...... y of Recurrent Neural Networks
@en
P2860
P50
P1476
A Three-Threshold Learning Rul ...... y of Recurrent Neural Networks
@en
P2093
Nicolas Brunel
P2860
P304
P356
10.1371/JOURNAL.PCBI.1004439
P577
2015-08-20T00:00:00Z
P5875
P698
P818
1508.00429