Semi-Supervised Junction Tree Variational Autoencoder for Molecular Property Prediction

1 code implementation • 10 Aug 2022 • Atia Hamidizadeh, Tony Shen, Martin Ester

We propose SeMole, a method that augments the Junction Tree Variational Autoencoders, a state-of-the-art generative model for molecular graphs, with semi-supervised learning.

Drug Discovery Molecular Property Prediction +3