Junction Tree Variational Autoencoder for Molecular Graph Generation

Implementation of our Junction Tree Variational Autoencoder https://arxiv.org/abs/1802.04364

Requirements

• Linux (We only tested on Ubuntu)
• RDKit (version >= 2017.09)
• Python (version >= 2.7)
• PyTorch (version >= 0.2)

To install RDKit, please follow the instructions here http://www.rdkit.org/docs/Install.html

We highly recommend you to use conda for package management.

Quick Start

This repository contains the following directories:

• bo/ includes scripts for Bayesian optimization experiments. Please read bo/README.md for details.
• molvae/ includes scripts for training our VAE model only. Please read molvae/README.md for training our VAE model.
• molopt/ includes scripts for jointly training our VAE and property predictors. Please read molopt/README.md for details.
• jtnn/ contains codes for model formulation.

Contact

Wengong Jin (wengong@csail.mit.edu)