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SchNetPack 2.0: A neural network toolbox for atomistic machine learning.
- Source :
- Journal of Chemical Physics; 4/14/2023, Vol. 158 Issue 14, p1-23, 23p
- Publication Year :
- 2023
-
Abstract
- SchNetPack is a versatile neural network toolbox that addresses both the requirements of method development and the application of atomistic machine learning. Version 2.0 comes with an improved data pipeline, modules for equivariant neural networks, and a PyTorch implementation of molecular dynamics. An optional integration with PyTorch Lightning and the Hydra configuration framework powers a flexible command-line interface. This makes SchNetPack 2.0 easily extendable with a custom code and ready for complex training tasks, such as the generation of 3D molecular structures. [ABSTRACT FROM AUTHOR]
- Subjects :
- MACHINE learning
MOLECULAR dynamics
MOLECULAR structure
LIGHTNING
Subjects
Details
- Language :
- English
- ISSN :
- 00219606
- Volume :
- 158
- Issue :
- 14
- Database :
- Complementary Index
- Journal :
- Journal of Chemical Physics
- Publication Type :
- Academic Journal
- Accession number :
- 163113548
- Full Text :
- https://doi.org/10.1063/5.0138367