thorben-frank / mlff
Build neural networks for machine learning force fields with JAX
☆110Updated last month
Alternatives and similar repositories for mlff:
Users that are interested in mlff are comparing it to the libraries listed below
- Equivariant machine learning interatomic potentials in JAX.☆71Updated last year
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆70Updated 2 years ago
- [TMLR 2023] Training and simulating MD with ML force fields☆111Updated 4 months ago
- train and use graph-based ML models of potential energy surfaces☆78Updated this week
- Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)☆46Updated last year
- LAMMPS pair style for Allegro deep learning interatomic potentials with parallelization support☆41Updated 4 months ago
- Higher-order equivariant neural networks for charge density prediction in materials☆50Updated 3 weeks ago
- SO3krates and Universal Pairwise Force Field for Molecular Simulation☆83Updated last month
- sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model☆147Updated last year
- MESS: Modern Electronic Structure Simulations☆27Updated 5 months ago
- Official implementation of DeepDFT model☆71Updated 2 years ago
- The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for organic molecules.☆63Updated 2 years ago
- [NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential☆42Updated last week
- Generate and predict molecular electron densities with Euclidean Neural Networks☆46Updated last year
- ☆17Updated 2 years ago
- A collection of QM data for training potential functions☆163Updated last month
- G-SchNet extension for SchNetPack☆56Updated 4 months ago
- ☆23Updated last year
- Collection of tutorials to use the MACE machine learning force field.☆43Updated 6 months ago
- repository and website for tutorials on 3d Euclidean equivariant neural networks☆71Updated 4 years ago
- Code for “From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction”.☆49Updated 4 months ago
- scalable molecular simulation☆130Updated last week
- Workflow for creating and analyzing the Open Catalyst Dataset☆106Updated last month
- High level API for using machine learning models in OpenMM simulations☆94Updated last week
- A unified framework for machine learning collective variables for enhanced sampling simulations☆99Updated last month
- cuEquivariance is a math library that is a collective of low-level primitives and tensor ops to accelerate widely-used models, like DiffD…☆194Updated this week
- MACE-OFF23 models☆31Updated last month
- High-performance operations for neural network potentials☆93Updated 2 weeks ago
- Higher order equivariant graph neural networks for 3D point clouds☆36Updated last year