This article pursues the insight that language models naturally enable an intelligent variation
operator similar in spirit to evolutionary crossover. In particular, language models of …

Abstract Denoising Autoencoder Genetic Programming (DAE-GP) is a model-based
evolutionary algorithm that uses denoising autoencoder long short-term memory networks …

Denoising autoencoder genetic programming (DAE-GP) is a novel neural network-based
estimation of distribution genetic programming approach that uses denoising autoencoder …

In standard genetic programming (stdGP), solutions are varied by modifying their syntax,
with uncertain effects on their semantics. Geometric-semantic genetic programming (GSGP) …

Denoising autoencoder genetic programming (DAE-GP) is an estimation of distribution
genetic programming (EDA-GP) algorithm. It uses denoising autoencoder long short-term …

Denoising Autoencoder Genetic Programming (DAE-GP) is a novel neural-network based
estimation of distribution genetic programming algorithm that uses denoising autoencoder …

Autoencoder models of source code are an emerging alternative to autoregressive large
language models with important benefits for genetic improvement of software. We …