natelgrw/AMAX-Models

AMAX Models: Molecular Absorption Wavelength Prediction

A collection of machine learning models for predicting maximum absorption wavelength (λ_max) of chemical compounds in various solvents. These models use molecular descriptors to predict spectroscopic properties, useful for drug discovery, materials science, and computational chemistry applications.

Version: 1.0.0

Source code for the AMAX model collection is available at this Github Repository.

The AMAX dataset is available at this Hugging Face Repository.

🤖 Available Models

Model	Architecture	Overall RMSE (nm)	Overall MAE (nm)	Overall R2
AMAX_XGB1	XGBoost	56.488	36.005	0.746
AMAX_MLP1	PyTorch Sequential MLP	64.152	44.388	0.669

All models were evaluated across rigorous scaffold, cluster, and method splits.

📄 Citation

If you use an AMAX prediction model in your research, please cite:

@modelcollection{amaxmodels,
  title={AMAX-Models: Machine Learning Models for Molecular Absorption Wavelength Prediction},
  author={Leung, Nathan},
  institution={Coley Research Group @ MIT}
  year={2025},
  howpublished={\url{https://huggingface.co/natelgrw/AMAX-Models}},
}