Skip to content
The Daily Repo

atomistic-machine-learning / schnetpack

SchNetPack - Deep Neural Networks for Atomistic Systems

Why this job: says: neural networks; topics: neural-network, machine-learning

What it does

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.

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Active
Last commit 3 days ago
Stars
943
On GitHub
Licence
Custom
Read before business use
Downloads for
None listed
No release files
Latest version
v2.3.0
Released 6 days ago
Built with
Python
98% of the code

Is it looked after?

Contributors
Not stated
Last 90 days
Issues
100% closed
1 still open
Pull requests
453 merged
2 waiting
Releases
12
2 in the last year
  • No contributing guide
  • No security policy
  • No code of conduct

Similar repos

Repos similar to this one
RepoStarsLast commitLicenceDownloads for
pytorch / pytorch105,450todayCustomNo downloads
PennyLaneAI / pennylane3,523todayApache-2.0No downloads
ARM-software / armnn1,3194 months agoMITLinux
More: languages, topics and project record

Languages

  • Python 98%
  • C++ 1%
  • Shell <1%

Topics

  • machine-learning
  • neural-network
  • quantum-chemistry
  • condensed-matter
  • molecular-dynamics

Project record

  • JobAI libraries and models
  • StatusListed
  • Commits1,915
  • Forks251
  • Watching27
  • Stars in 28 days+1
  • CreatedSep 3, 2018
  • First seen by usNov 7, 2026
  • CheckedNov 10, 2026

Type to search.

Try