Experimental demonstration of soft-failure management using variational autoencoder and GAN on optical spectrum

We show combined soft-failure detection, identification und localization enabled by machine learning using experimentally obtained optical spectra as inputs. Our VAE and GAN-based framework shows high F1-scores requiring only 6% of total training data while being able to identify unknown failure spectra with 99.81% accuracy.