mir-group / allegroLinks
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
☆432Updated last month
Alternatives and similar repositories for allegro
Users that are interested in allegro are comparing it to the libraries listed below
Sorting:
- NequIP is a code for building E(3)-equivariant interatomic potentials☆792Updated 2 weeks ago
- 🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.☆555Updated this week
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆887Updated 2 weeks ago
- Torch-native, batchable, atomistic simulations.☆286Updated last week
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆330Updated 2 weeks ago
- Graph deep learning library for materials☆429Updated last week
- Neural Network Force Field based on PyTorch☆281Updated last month
- An open-source Python package for creating fast and accurate interatomic potentials.☆335Updated 3 weeks ago
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆193Updated this week
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆444Updated last week
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆296Updated 6 months ago
- Training neural network potentials☆439Updated 3 weeks ago
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆429Updated 2 weeks ago
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary☆282Updated last month
- End-To-End Molecular Dynamics (MD) Engine using PyTorch☆661Updated 8 months ago
- ORB forcefield models from Orbital Materials☆497Updated last week
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆193Updated 3 weeks ago
- SchNet - a deep learning architecture for quantum chemistry☆265Updated 7 years ago
- A code to generate atomic structure with symmetry☆336Updated 2 weeks ago
- The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field☆361Updated last week
- atomate2 is a library of computational materials science workflows☆244Updated this week
- Converts an xyz file to an RDKit mol object☆277Updated 8 months ago
- [ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations☆292Updated 7 months ago
- A collection of Nerual Network Models for chemistry☆162Updated 3 weeks ago
- A toolkit for visualizations in materials informatics.☆275Updated 2 weeks ago
- n2p2 - A Neural Network Potential Package☆239Updated 6 months ago
- Matbench: Benchmarks for materials science property prediction☆167Updated last year
- An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]☆328Updated last year
- i-PI: a universal force engine☆271Updated this week
- DMFF (Differentiable Molecular Force Field) is a Jax-based python package that provides a full differentiable implementation of molecular…☆180Updated 3 weeks ago