Mingjian Wen's repositories
geodesicLM
Geodesic Levenberg-Marquardt minimization algorithm
DRIP_WenTadmor__MD_000000111111_000
KIM driver of the DRIP potential.
atomate
atomate is a powerful software for computational materials science and contains pre-built workflows.
atomate2
atomate2 is a library of computational materials science workflows
custom-wowchemy-theme
My settings for Hugo Academic (wowchemy)
dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
DRIP_WenTadmor_2018_C__MO_000000111111_000
KIM model of the DRIP potential.
dscribe
DScribe is a python package for creating machine learning descriptors for atomistic systems.
DUNN__MD_000000111111_000
KIM model driver for Dropout Uncertainty Neural Network (DUNN) interatomic potential
DUNN_WenTadmor_2019v1_C__MO_000000111111_000
KIM model for Dropout Uncertainty Neural Network (DUNN) interatomic potential
e3nn
A modular framework for neural networks with Euclidean symmetry
fireworks
The Fireworks Workflow Management Repo.
hNN__MD_435082866799_000
A KIM model driver of the hybrid neural network potential.
hNN_WenTadmor_2019Grx_C__MO_421038499185_000
A KIM model of the hybrid neural network potential.
jobflow
jobflow is a library for writing computational workflows.
kim-api
The Open Knowledgebase of Interatomic Models (OpenKIM) aims to be an online resource for standardized testing, long-term warehousing and easy retrieval of interatomic models and data.
kim-nequip
Small utility fork of nequip to port NequIP models to OpenKIM compatible format
maggma
MongoDB aggregation machine
mjwen.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
pymatgen
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project.
schnetpack
SchNetPack - Deep Neural Networks for Atomistic Systems