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

<p>Simulated neutron spectra from inelastic neutron scattering on the double perovskite PCSMO. The dataset is related to the publication <em>Interpretable, calibrated neural networks for analysis and understanding of neutron spectra</em>. The paper is yet to be submitted, but the references will be added in due course.</p> <p># Pre-trained model weights</p> <p>`model-weights.tgz`</p> <p>This file contains the weights for the models reported in the paper which can be downloaded and used to re-produce the results.</p> <p>Please download the `model-weights.tgz` file and extract it to the root of the repository `interpretable-ml-neutron-spectroscopy` from github.</p> <p># Data Generation</p> <p>`data_generation.tar.gz`</p> <p>&nbsp;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.</p> <p>Please download the `data_generation.tar.gz` file and extract it to the root of the repository `interpretable-ml-neutron-spectroscopy` from github.</p> <p>#Training data</p> <p>`<a href="https://zenodo.org/api/files/47a40b89-ae6f-4655-aa4b-2d8fc11ec597/pcsmo-simulated-spectra.tgz?versionId=1ff107a9-85b9-4b46-9c77-84319ca9d59a">pcsmo-simulated-spectra.tgz</a>`</p> <p>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 `&lt;datadir&gt;` in the specified location in those files.</p>