Before revision:  Our results indicate  many molecular problems stand to gain from three-dimensional molecular learning . All code and datasets can be accessed via URL .
After revision:  Our results indicate many molecular problems stand to gain from three-dimensional molecular learning , and that there is potential for improvement on many tasks which remain underexplored. To lower the barrier to entry and facilitate further developments in the field, we also provide a comprehensive suite of tools for dataset processing, model training, and evaluation in our open-source atom3d Python package. All datasets are available for download from URL .