Zeng et al. use a neural network to optimize approximate GKP codewords, requiring fewer large-amplitude states while enhancing error correction under photon loss and dephasing. Their method outperforms standard constructions at common squeezing levels. https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.134.060601