Generalizable QoT Estimation Based on Spectral Data Driven LSTM in Exact Component Parameter Agnostic Networks

We investigate the robustness of our spectral data driven machine learning based QoT estimator by artificially noising the input features. The estimator shows superior robustness against feature changes compared to a non-spectral estimator. We validate its generalization ability and robustness on an unseen experimental dataset.