Training of AI Surrogate Models

This repository contains the current experiments for training AI models that attempt to predict the chemistry component of POET and is structued as follows:

└── dataset
    └── Barite_50_Data_training.h5
    └── barite_50_4_corner.h5
└── doc
└── results
└── src
    └── POET_Training.ipynb
    └── convert_data.jl
    └── optuna_runs.py
    └── preprocessing.py

The datasets in datasets must first be pulled via git lfs pull to get the data from the large file storage. A conda environment can then be set up with the packages contained in environment.yml with conda env create -f environment.yml

The preprocessing.py file defines all the necessary steps for preprocessing as well as the keras models used. The actual training and additional explanations then take place in POET_Training.ipynb.