  Autoencoder-based deep learning is applied to jointly optimize geometric and
probabilistic constellation shaping for optical coherent communication. The
optimized constellation shaping outperforms the 256 QAM Maxwell-Boltzmann
probabilistic distribution with extra 0.05 bits/4D-symbol mutual information
for 64 GBd transmission over 170 km SMF link.
