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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-99191-2 |