mir-group / nequipLinks
NequIP is a code for building E(3)-equivariant interatomic potentials
☆819Updated this week
Alternatives and similar repositories for nequip
Users that are interested in nequip are comparing it to the libraries listed below
Sorting:
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆930Updated last week
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆440Updated 2 months ago
- 🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.☆577Updated this week
- SchNetPack - Deep Neural Networks for Atomistic Systems☆886Updated this week
- Graph deep learning library for materials☆464Updated this week
- Training neural network potentials☆447Updated 2 months ago
- End-To-End Molecular Dynamics (MD) Engine using PyTorch☆670Updated 10 months ago
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆451Updated last month
- Neural Network Force Field based on PyTorch☆281Updated 2 months ago
- An open-source Python package for creating fast and accurate interatomic potentials.☆339Updated 2 months ago
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆343Updated 3 weeks ago
- SchNet - a deep learning architecture for quantum chemistry☆270Updated 7 years ago
- An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]☆344Updated last year
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆437Updated 2 weeks ago
- Torch-native, batchable, atomistic simulations.☆353Updated this week
- Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals☆545Updated 2 years ago
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆302Updated 7 months ago
- The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field☆368Updated last week
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary☆287Updated 2 months ago
- TorchANI 2.0 is an open-source library that supports training, development, and research of ANI-style neural network interatomic potentia…☆528Updated this week
- ORB forcefield models from Orbital Materials☆513Updated last week
- [ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations☆303Updated 9 months ago
- A repository of update in molecular dynamics field by recent progress in machine learning and deep learning.☆326Updated 4 years ago
- Crystal graph convolutional neural networks for predicting material properties.☆790Updated 4 years ago
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆201Updated this week
- cuEquivariance is a math library that is a collective of low-level primitives and tensor ops to accelerate widely-used models, like DiffD…☆324Updated this week
- Semiempirical Extended Tight-Binding Program Package☆718Updated last week
- DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Awa…☆343Updated 2 years ago
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆199Updated last week
- A code to generate atomic structure with symmetry☆345Updated this week