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Optical Phase Dropout in Diffractive Deep Neural Network
To address the overfitting problem that comes from the small samples loaded to [DN]2, an optical phase dropout trick is implemented.
Unitary Learning for Deep Diffractive Neural Network
Realization of deep learning with coherent diffraction has achieved remarkable development nowadays, which benefits on the fact that matrix multiplication can be optically executed in parallel as well as with little power consumption.
Compatible Learning for Deep Photonic Neural Network
Realization of deep learning with coherent optical field has attracted remarkably attentions presently, which benefits on the fact that optical matrix manipulation can be executed at speed of light with inherent parallel computation as well as low latency.
