Alternatives and similar repositories for mace

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

• mir-group / nequip
  NequIP is a code for building E(3)-equivariant interatomic potentials
  ☆847Updated last week
• JuDFTteam / best-of-atomistic-machine-learning
  🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
  ☆603Updated this week
• mir-group / allegro
  Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
  ☆455Updated 3 weeks ago
• materialyzeai / matgl
  Graph deep learning library for materials
  ☆499Updated 2 weeks ago
• CederGroupHub / chgnet
  Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov
  ☆356Updated 2 months ago
• SINGROUP / dscribe
  DScribe is a python package for creating machine learning descriptors for atomistic systems.
  ☆456Updated 3 months ago
• mir-group / flare
  An open-source Python package for creating fast and accurate interatomic potentials.
  ☆342Updated 4 months ago
• materialyzeai / maml
  Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
  ☆446Updated 2 weeks ago
• atomistic-machine-learning / schnetpack
  SchNetPack - Deep Neural Networks for Atomistic Systems
  ☆904Updated last week
• deepmodeling / dpgen
  The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field
  ☆374Updated last week
• TorchSim / torch-sim
  Torch-native, batchable, atomistic simulations.
  ☆397Updated this week
• learningmatter-mit / NeuralForceField
  Neural Network Force Field based on PyTorch
  ☆284Updated 4 months ago
• materialyzeai / m3gnet
  Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.
  ☆311Updated 9 months ago
• txie-93 / cdvae
  An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
  ☆353Updated last year
• torchmd / torchmd-net
  Training neural network potentials
  ☆461Updated 2 weeks ago
• mzjb / DeepH-pack
  Deep neural networks for density functional theory Hamiltonian.
  ☆314Updated last year
• usnistgov / alignn
  Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary
  ☆294Updated 4 months ago
• janosh / pymatviz
  A toolkit for visualizations in materials informatics.
  ☆297Updated last week
• torchmd / torchmd
  End-To-End Molecular Dynamics (MD) Engine using PyTorch
  ☆676Updated 2 weeks ago
• grimme-lab / xtb
  Semiempirical Extended Tight-Binding Program Package
  ☆738Updated last month
• MDIL-SNU / SevenNet
  SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.
  ☆210Updated 2 weeks ago
• txie-93 / cgcnn
  Crystal graph convolutional neural networks for predicting material properties.
  ☆815Updated 4 years ago
• materialsproject / atomate2
  atomate2 is a library of computational materials science workflows
  ☆265Updated last week
• CompPhysVienna / n2p2
  n2p2 - A Neural Network Potential Package
  ☆240Updated 10 months ago
• MaterSim / PyXtal
  A code to generate atomic structure with symmetry
  ☆353Updated last week
• i-pi / i-pi
  i-PI: a universal force engine
  ☆284Updated 2 months ago
• orbital-materials / orb-models
  ORB forcefield models from Orbital Materials
  ☆529Updated last week
• materialyzeai / megnet
  Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
  ☆551Updated 2 years ago
• atomistic-machine-learning / SchNet
  SchNet - a deep learning architecture for quantum chemistry
  ☆281Updated 7 years ago
• janosh / matbench-discovery
  An evaluation framework for machine learning models simulating high-throughput materials discovery.
  ☆206Updated this week