name: schnetpack
description: SchNetPack aims to provide accessible atomistic neural networks that can be trained and applied out-of-the-box, while still being extensible to custom atomistic architectures.
license_spdx: MIT
version: 0.3
spec_version: 1.0
download_url: https://conda.anaconda.org/conda-forge/noarch/schnetpack-0.3-py_0.tar.bz2
home_url: https://github.com/atomistic-machine-learning/schnetpack
news_url: https://libraries.io/conda/schnetpack/versions.atom
date: 2019-09-17
about_resource: NONE
libraries_io_url: https://libraries.io/conda/schnetpack?number=0.3
vcs_tool: git
vcs_repository: https://github.com/atomistic-machine-learning/schnetpack
vcs_branch: master
