most citedTraining End-to-End Analog Neural Networks with Equilibrium Propagation

41 citations · 41 across the 1 of their papers we have counts for

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1 paper

cs.NE2020★ 41 cited

Training End-to-End Analog Neural Networks with Equilibrium Propagation

Jack Kendall, Ross Pantone, Kalpana Manickavasagam +2

We introduce a principled method to train end-to-end analog neural networks by stochastic gradient descent. In these analog neural networks, the weights to be adjusted are implemen…