Probabilistic photonic computing with chaotic light

HIGHLIGHTS

• What: Next, the authors investigate the behavior of independent samples drawn from the four WDM wavelength channels shown in Fig 2c when sampling is performed in parallel. Next, the authors investigate the accumulation, i.e. addition, of two input distributions. The authors design a modified LeNet-532 deep neural_network architecture, shown in Fig 5a, and deploy the MNIST dataset for training and benchmarking. The authors compare the OOD detection of the BNN with different deterministic methods like Maximum Predicted Nature Communications | 15:10445 Training Data: determinis c probabilis c Class "6" Counts 84 Fully Connected Output Score . . .
  

   

  

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