Autoencoder models of source code are an emerging alternative to autoregressive large language models with important benefits for genetic improvement of software. We hypothesize that encoder-decoder ...

A Convolutional Variational Autoencoder (CVAE) was developed for this purpose. We demonstrate the efficacy of our approach using the transient data generated from the simulations. The simulation data ...

This repository includes two Jupyter notebooks to assist with data preparation, model training, and performance evaluation: AE.ipynb: This notebook provides a step-by-step guide for preparing the ...

2.2.2 Variational autoencoder (VAE) VAE is a probabilistic variant of AE, that uses variational lower bound of the marginal likelihood, based on Bayesian inference, to identify multivariate patterns ...