Alternatives and similar repositories for megnet

Users that are interested in megnet are comparing it to the libraries listed below

• SINGROUP / dscribe
  DScribe is a python package for creating machine learning descriptors for atomistic systems.
  ☆444Updated 2 months ago
• atomistic-machine-learning / schnetpack
  SchNetPack - Deep Neural Networks for Atomistic Systems
  ☆869Updated 2 weeks ago
• materialsvirtuallab / maml
  Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
  ☆428Updated 2 weeks ago
• txie-93 / cgcnn
  Crystal graph convolutional neural networks for predicting material properties.
  ☆776Updated 4 years ago
• materialsvirtuallab / matgl
  Graph deep learning library for materials
  ☆420Updated this week
• atomistic-machine-learning / SchNet
  SchNet - a deep learning architecture for quantum chemistry
  ☆262Updated 7 years ago
• mir-group / nequip
  NequIP is a code for building E(3)-equivariant interatomic potentials
  ☆785Updated last week
• materialsvirtuallab / m3gnet
  Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.
  ☆295Updated 5 months ago
• JuDFTteam / best-of-atomistic-machine-learning
  🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
  ☆546Updated last week
• ACEsuit / mace
  MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
  ☆872Updated last week
• torchmd / torchmd
  End-To-End Molecular Dynamics (MD) Engine using PyTorch
  ☆659Updated 8 months ago
• aiqm / torchani
  Accurate Neural Network Potential on PyTorch
  ☆511Updated last week
• mir-group / flare
  An open-source Python package for creating fast and accurate interatomic potentials.
  ☆334Updated last week
• mir-group / allegro
  Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
  ☆430Updated last week
• deepmodeling / dpgen
  The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field
  ☆357Updated this week
• hackingmaterials / matminer
  Data mining for materials science
  ☆546Updated last month
• learningmatter-mit / NeuralForceField
  Neural Network Force Field based on PyTorch
  ☆281Updated 2 weeks ago
• usnistgov / alignn
  Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary
  ☆278Updated 3 weeks ago
• txie-93 / cdvae
  An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
  ☆323Updated last year
• CederGroupHub / chgnet
  Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov
  ☆329Updated this week
• Fung-Lab / MatDeepLearn
  MatDeepLearn, package for graph neural networks in materials chemistry
  ☆197Updated 2 years ago
• gasteigerjo / dimenet
  DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Awa…
  ☆337Updated last year
• jparkhill / TensorMol
  Tensorflow + Molecules = TensorMol
  ☆275Updated 4 years ago
• torchmd / torchmd-net
  Training neural network potentials
  ☆432Updated last week
• hackingmaterials / automatminer
  An automatic engine for predicting materials properties.
  ☆163Updated last year
• materialsvirtuallab / matgenb
  Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.
  ☆260Updated 2 weeks ago
• Tony-Y / cgnn
  Crystal Graph Neural Networks
  ☆108Updated last year
• TUM-DAML / gemnet_pytorch
  GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)
  ☆212Updated 2 years ago
• isayev / ASE_ANI
  ANI-1 neural net potential with python interface (ASE)
  ☆223Updated last year
• janosh / pymatviz
  A toolkit for visualizations in materials informatics.
  ☆274Updated this week