Introduction

This package provide fast and accurate machine learning models for biochemical applications. Especially, we support very high-dimensional models with sparse inputs, e.g., millions of features and millions of compounds.

• The general documentation can be found here.
• Documentation about how to retrain a pretrained model can be found here.
• Documentation about how to profile GPU memory usage and use mixed precision can be found here.
• Documentation about how to use Catalogue Fusion can be found here.

Reference

If you use this software in your work, please cite:

@article{arany2022sparsechem,
  title={SparseChem: Fast and accurate machine learning model for small molecules},
  author={Arany, Adam and Simm, Jaak and Oldenhof, Martijn and Moreau, Yves},
  journal={arXiv preprint arXiv:2203.04676},
  year={2022}
}