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TRAINING OF PHOTONIC NEURAL NETWORKS THROUGH IN SITU BACKPROPAGATION
TRAINING OF PHOTONIC NEURAL NETWORKS THROUGH IN SITU BACKPROPAGATION
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机译:通过原位反向化训练光子神经网络
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摘要
Systems and methods for training photonic neural networks in accordance with embodiments of the invention are illustrated. One embodiment includes a method for training a set of one or more optical interference units (OIUs) of a photonic artificial neural network (ANN), wherein the method includes calculating a loss for an original input to the photonic ANN, computing an adjoint input based on the calculated loss, measuring intensities for a set of one or more phase shifters in the set of OIUs when the computed adjoint input and the original input are interfered with each other within the set of OIUs, computing a gradient from the measured intensities, and tuning phase shifters of the OIU based on the computed gradient.
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