Published October 14, 2020 | Version v2
Dataset Open

Data/code for Interpretable, calibrated neural networks for analysis and understanding of neutron spectra

  • 1. Rutherford Appleton Laboratory

Description

Simulated neutron spectra from inelastic neutron scattering on the double perovskite PCSMO. The dataset is related to the publication Interpretable, calibrated neural networks for analysis and understanding of neutron spectra. The paper is yet to be submitted, but the references will be added in due course.

# Pre-trained model weights

`model-weights.tgz`

This file contains the weights for the models reported in the paper which can be downloaded and used to re-produce the results.

Please download the `model-weights.tgz` file and extract it to the root of the repository `interpretable-ml-neutron-spectroscopy` from github.

# Data Generation

`data_generation.tar.gz`

 Large data files for github repository associated with the publication _Interpretable, calibrated neural networks for analysis and understanding of neutron spectra_ These files relate to generation of the data in the paper.

Please download the `data_generation.tar.gz` file and extract it to the root of the repository `interpretable-ml-neutron-spectroscopy` from github.

#Training data

`pcsmo-simulated-spectra.tgz`

Contains the data used to train the networks. Extract this file to a data directory and then point the `train.py` files for the various models to look for this `<datadir>` in the specified location in those files.

Files

Files (12.7 GB)

Name Size Download all
md5:0c67e2f312056c3ba0f476ffecab33a8
947.1 MB Download
md5:640c2364f0096557383a8688f3ef7043
2.0 GB Download
md5:ccf41f0dac8f2bfde2c82e4e8a4a0c67
9.8 GB Download