An adiabatic method to train binarized artificial neural networks

Abstract An artificial neural network consists of neurons and synapses. Neuron gives output based on its input according to non-linear activation functions such as the Sigmoid, Hyperbolic Tangent (Tanh), or Rectified Linear Unit (ReLU) functions, etc.. Synapses connect the neuron outputs to their in...

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Autores principales: Yuansheng Zhao, Jiang Xiao
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/1e37ac851b52403d9e4e101a2e68ed61
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