Neural Architecture Search (NAS) has emerged as a powerful technique for automatically designing neural network architectures, offering the potential to discover models with superior performance and efficiency compared to manually designed architectures. In this study, we explore the application of NAS to autoencoder architectures, aiming to find models that provide the best trade-off between mode...Show More
