pfnet-research / torch-dftdLinks
pytorch implementation of dftd2 & dftd3 (not actively maintained)
☆91Updated 3 weeks ago
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 systems☆73Updated this week
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆88Updated last week
- Collection of tutorials to use the MACE machine learning force field.☆51Updated 2 weeks ago
- Quick Uncertainty and Entropy via STructural Similarity☆56Updated 3 weeks ago
- Deprecated - see `pair_nequip_allegro`☆44Updated 9 months ago
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆96Updated last month
- MACE_Osaka24 models☆25Updated last year
- Computing representations for atomistic machine learning☆75Updated last week
- Particle-mesh based calculations of long-range interactions in PyTorch☆70Updated last week
- A framework for performing active learning for training machine-learned interatomic potentials.☆39Updated 2 months ago
- ☆32Updated 4 months ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆85Updated 3 years ago
- train and use graph-based ML models of potential energy surfaces☆119Updated last month
- graph2mat: Graph to matrix conversion☆19Updated 2 weeks ago
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integr…☆58Updated 2 months ago
- Alchemical machine learning interatomic potentials☆33Updated last year
- ☆22Updated last year
- ☆41Updated last week
- python workflow toolkit☆43Updated last month
- UF3: a python library for generating ultra-fast interatomic potentials☆70Updated 7 months ago
- Active Learning for Machine Learning Potentials☆63Updated 2 months ago
- Train, fine-tune, and manipulate machine learning models for atomistic systems☆54Updated last week
- Collection of Tutorials on Machine Learning Interatomic Potentials☆25Updated last year
- The Wren sits on its Roost in the Aviary.☆61Updated 3 weeks ago
- Generative materials benchmarking metrics, inspired by guacamol and CDVAE.☆41Updated last year
- Code for automated fitting of machine learned interatomic potentials.☆134Updated 2 weeks ago
- ☆117Updated 3 weeks ago
- A Python software package for saddle point optimization and minimization of atomic systems.☆129Updated 2 weeks ago
- Atomistic machine learning models you can use everywhere for everything☆33Updated last week
- Descriptors (isometry invariants) of crystals based on geometry.☆37Updated 2 months ago