Device-Informed Training Strategy for Low-Precision Photonic Neural Networks

This paper compares three training strategies for low-precision photonic neural networks. The efficacy of the schemes is tested through circuital simulations on the photonic electronic multiplyaccumulate neuron (PEMAN) architecture with three different datasets.