This repository reproduces "Complex-valued neural networks for machine learning on non-stationary physical data".
Obtained from https://github.com/olivesgatech/facies_classification_benchmark via
# download the files:
wget https://zenodo.org/record/3755060/files/data.zip
# check that the md5 checksum matches:
openssl dgst -md5 data.zip # Make sure the result looks like this: MD5(data.zip)= bc5932279831a95c0b244fd765376d85, otherwise the downloaded data.zip is corrupted.
Preparation for training via src/data_prep.py.
Training done on GPU cluster using src/mass_train.py.
Use trained models to generate predictions src/save_predictions.py.
Numerical and qualitative analysis generated via src/explore.py.
Please cite the according paper as
@article{dramsch2020complex,
title={Complex-valued neural networks for machine learning on non-stationary physical data},
author={Dramsch, Jesper S{\"o}ren and L{\"u}thje, Mikael and Christensen, Anders Nymark},
journal={Computers \& Geosciences},
pages={104643},
year={2020},
publisher={Elsevier}
}