mdsunivie / deeperwin

DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electron Schrödinger equation. DeepErwin supports weight-sharing when optimizing wave functions for multiple nuclear geometries and the usage of pre-trained neural network weights to accelerate optimization.

Date Created 2021-06-14 (3 years ago)

Commits 66 (last one 5 months ago)

Stargazers 53 (0 this week)

Watchers 2 (0 this week)

Forks 7

License other

Ranking

RepositoryStats indexes 584,777 repositories, of these mdsunivie/deeperwin is ranked #445,464 (24th percentile) for total stargazers, and #478,954 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #84,831/116,437.

mdsunivie/deeperwin is also tagged with popular topics, for these it's ranked: deep-learning (#6,814/8398), deep-neural-networks (#532/627), transfer-learning (#245/311)

Other Information

mdsunivie/deeperwin has 1 open pull request on Github, 4 pull requests have been merged over the lifetime of the repository.

There have been 3 releases, the latest one was published on 2024-03-25 (8 months ago) with the name Transferable atomic orbitals.

All Topics

deep-learning physical-chem weight-sharing transfer-learning quantum-monte-carlo deep-neural-networks schrodinger-equation variational-monte-carlo

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32 commits on the default branch (master) since jan '22

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The only known language in this repository is Python

updated: 2024-11-21 @ 05:46pm, id: 376868395 / R_kgDOFnaOKw