Syntax-Directed Variational Autoencoder for Structured Data

Advances in deep learning of representation have resulted in powerful generative approaches on modeling continuous data like time series and images, but it is still challenging to correctly deal with discrete structured data, such as chemical molecules and computer programs. To tackle these challenges, there has been many improvements in formalization of structure generation that … Continue reading Syntax-Directed Variational Autoencoder for Structured Data