SchNetPack is a toolbox for the development and application of deep neural networks to the prediction of potential energy surfaces and other quantum-chemical properties of molecules and materials. It contains basic building blocks of atomistic neural networks, manages their training and provides simple access to common benchmark datasets. This allows for an easy implementation and evaluation of new models.
Schutt, K. T., et al. "SchNetPack: A deep learning toolbox for atomistic systems." Journal of chemical theory and computation 15.1 (2018): 448-455.
Deep Learning, CNN,
Curator: qinyang