Files for Training/Inferencing Mixture-of-Experts Transformers for Deorbitalized Meta-GGA Density Functionals

This dataset contains the pre-processing, training and inference files to learn deorbitalized surrogate models for orbital-dependent, semi-local meta-GGA exchange correlation functionals using Mixture-of-Experts transformers. Expert domains are defined using K-means clustering of principal components of orbital-dependent functional predictions. Expert models are trained using a transfer learning protocol of pre-training and fine-tuning. A gating network is trained to route integration grid points to each expert model. The files in the "Inference" and "System Input Files" directories are required to run the model scripts in "<i>https://github.com/amitmc1/MetaGGA-Transformers/tree/main/Inference</i>".