dft-dutoit / XPOTLinks
Cross-platform Optimizer for ML Interatomic Potentials
☆21Updated 3 months ago
Alternatives and similar repositories for XPOT
Users that are interested in XPOT are comparing it to the libraries listed below
Sorting:
- ☆33Updated last week
- Some tutorial-style examples for validating machine-learned interatomic potentials☆34Updated 2 years ago
- Tools for machine learnt interatomic potentials☆41Updated last week
- Quick Uncertainty and Entropy via STructural Similarity☆54Updated last week
- A collection of files related to machine learning force fields☆23Updated 2 years ago
- MACE_Osaka24 models☆23Updated last year
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆16Updated last year
- Alchemical machine learning interatomic potentials☆32Updated last year
- Phonons from ML force fields☆23Updated 5 months ago
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integr…☆54Updated last month
- ☆21Updated last year
- Graph neural network prediction of electronic Hamiltonians in atomic orbital representation with many body messages☆24Updated 2 months ago
- python workflow toolkit☆45Updated this week
- ☆11Updated last year
- Tutorial exercises for the OPTIMADE API☆17Updated 2 years ago
- ☆28Updated 5 months ago
- A molecular simulation package integrating MLFFs in MOFs for DAC☆41Updated 2 months ago
- materials science related animations☆13Updated 11 months ago
- Active Learning for Machine Learning Potentials☆63Updated last month
- Random symmetric initialization of crystals☆23Updated 7 years ago
- Heat-conductivity benchmark test for foundational machine-learning potentials☆29Updated 4 months ago
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆84Updated this week
- ⚛ download and manipulate atomistic datasets☆48Updated last month
- dataset augmentation for atomistic machine learning☆21Updated last month
- `quansino` is a modular package based on the Atomic Simulation Environment (ASE) for quickly building custom Monte Carlo algorithms☆28Updated last week
- ☆12Updated last month
- Global Optimizer for Clusters, Interfaces, and Adsorbates☆31Updated last week
- Calculation of vibrational spectra with quantum nuclear motion☆12Updated last year
- Python package to interact with high-dimensional representations of the chemical elements☆47Updated last week
- A Benchmarking Framework for Crystal GNNs☆20Updated last year