Tag: Variational Autoencoders

AI Machine Learning & Data Science Research

Georgia Tech & Google Propose a Novel Discrete Variational Autoencoder for Automatically Improving Code Efficiency

In the new paper Learning to Improve Code Efficiency, a research team from the Georgia Institute of Technology and Google Research presents a novel discrete generative latent-variable model designed to help programmers identify more computationally efficient code variants, taking a step toward automating the process of code performance optimization.