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: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/1e37ac851b52403d9e4e101a2e68ed61 |
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