Equivalence of Equilibrium Propagation and Recurrent BackpropagationEIWOS

    Benjamin Scellier
    Benjamin Scellier
    Cited by: 3|Bibtex|22|

    Neural computation, Volume abs/1711.08416, Issue 2, 2018, Pages 312-329.

    Abstract:

    Recurrent backpropagation and equilibrium Propagation are supervised learning algorithms for fixed-point recurrent neural networks, which differ in their second phase. In the first phase, both algorithms converge to a fixed point that corresponds to the configuration where the prediction is made. In the second phase, equilibrium propagati...More
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