pfnet-research / torch-dftdLinks
pytorch implementation of dftd2 & dftd3 (not actively maintained)
β88Updated last year
Alternatives and similar repositories for torch-dftd
Users that are interested in torch-dftd are comparing it to the libraries listed below
Sorting:
- Compute neighbor lists for atomistic systemsβ68Updated 2 weeks ago
- π [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics β¦β84Updated this week
- MACE_Osaka24 modelsβ23Updated last year
- Collection of tutorials to use the MACE machine learning force field.β50Updated last year
- Quick Uncertainty and Entropy via STructural Similarityβ54Updated last week
- python workflow toolkitβ45Updated this week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIPβ¦β96Updated 2 weeks ago
- train and use graph-based ML models of potential energy surfacesβ117Updated last week
- Particle-mesh based calculations of long-range interactions in PyTorchβ65Updated last week
- Computing representations for atomistic machine learningβ74Updated 3 weeks ago
- Deprecated - see `pair_nequip_allegro`β44Updated 8 months ago
- UF3: a python library for generating ultra-fast interatomic potentialsβ68Updated 6 months ago
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integrβ¦β54Updated last month
- β33Updated last week
- β32Updated 2 months ago
- Alchemical machine learning interatomic potentialsβ32Updated last year
- Collection of Tutorials on Machine Learning Interatomic Potentialsβ23Updated last year
- A framework for performing active learning for training machine-learned interatomic potentials.β39Updated last month
- β21Updated last year
- β download and manipulate atomistic datasetsβ48Updated last month
- Active Learning for Machine Learning Potentialsβ63Updated last month
- graph2mat: Graph to matrix conversionβ18Updated 2 months ago
- Atomistic machine learning models you can use everywhere for everythingβ32Updated last week
- ALCHEMI Toolkit-Ops is a collection of optimized batch kernels to accelerate computational chemistry and material science workflows.β46Updated last week
- Heat-conductivity benchmark test for foundational machine-learning potentialsβ29Updated 4 months ago
- Symmetry-Adapted Learning of Three-dimensional Electron Densities (and their electrostatic response)β40Updated last week
- Code for automated fitting of machine learned interatomic potentials.β133Updated last week
- Descriptors (isometry invariants) of crystals based on geometry.β36Updated last month
- Moment Invariants Local Atomic Descriptorβ34Updated last year
- A Python software package for saddle point optimization and minimization of atomic systems.β123Updated 3 months ago