Skip to content

Repository files navigation

Graph LDA : Graph Latent Diffusion Autoencoder

The official implementation of Graph LDA : Graph latent diffusion-based molecular representation learning for enhanced generalization in molecular property prediction

Publication

J.Cheminfo

Requirements

  • Python 3.10.13
  • PyTorch 2.4.0
  • Pytorch geometric 2.5.3
  • networkx 3.1
  • RDKit version 2024.3.5.0

Dataset and Trained Models

Dataset and pre-trained models in our experiments are avaiable here.

About Scripts

As mentioned in our paper, we use PIG-VAE for molecular graph autoencoder architecture. The code for the PIG-VAE can be found in pigvae_all/pigvae.

About

Core code for Graph Latent Diffusion Autoencoder

Resources

Stars

2 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages