Neuroevolution with genetic algorithms and particle swarm optimization can train simulated optical neural networks to accuracies comparable to gradient-based methods on small classification tasks.
On-Chip Optical Convolutional Neural Networks
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abstract
Convolutional Neural Networks (CNNs) are a class of Artificial Neural Networks(ANNs) that employ the method of convolving input images with filter-kernels for object recognition and classification purposes. In this paper, we propose a photonics circuit architecture which could consume a fraction of energy per inference compared with state of the art electronics.
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2019 1verdicts
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Efficient training and design of photonic neural network through neuroevolution
Neuroevolution with genetic algorithms and particle swarm optimization can train simulated optical neural networks to accuracies comparable to gradient-based methods on small classification tasks.