dario-coscia / blipLinks
This repository contains the source code for Bayesian Learned Interatomic Potentials (BLIP)
☆28Updated 2 months ago
Alternatives and similar repositories for blip
Users that are interested in blip are comparing it to the libraries listed below
Sorting:
- ☆11Updated last year
- Tools for machine learnt interatomic potentials☆39Updated 3 weeks ago
- dataset augmentation for atomistic machine learning☆20Updated 4 months ago
- Modulated automation of cluster expansion based on atomate2 and Jobflow☆12Updated this week
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆21Updated last year
- ☆27Updated 2 months ago
- Cross-platform Optimizer for ML Interatomic Potentials☆20Updated 2 months ago
- Adds Orb Model functionality to LAMMPS via Python wrapping☆15Updated 6 months ago
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆16Updated last year
- Alchemical machine learning interatomic potentials☆31Updated 11 months ago
- MACE_Osaka24 models☆20Updated 10 months ago
- Quick Uncertainty and Entropy via STructural Similarity☆50Updated last month
- python workflow toolkit☆43Updated this week
- NIST Interatomic Potential Repository property calculation tools☆12Updated 2 months ago
- a find-and-replace tool for crystal structure models. implements (i) subgraph matching and (ii) point set alignment to search a parent cr…☆18Updated last year
- Collection of Tutorials on Machine Learning Interatomic Potentials☆23Updated last year
- ☆34Updated last year
- materials science related animations☆13Updated 9 months ago
- A collection of simulation recipes for the atomic-scale modeling of materials and molecules☆30Updated this week
- Training Neural Network potentials through customizable routines in JAX.☆54Updated 3 months ago
- Train, fine-tune, and manipulate machine learning models for atomistic systems☆45Updated last week
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integr…☆48Updated last month
- Tutorial to learn basic features of atomate2☆14Updated last year
- ⚛ download and manipulate atomistic datasets☆47Updated 2 weeks ago
- Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics https://arxiv.org/abs/2509.…☆77Updated last week
- Some tutorial-style examples for validating machine-learned interatomic potentials☆34Updated last year
- ☆17Updated 7 months ago
- Compute neighbor lists for atomistic systems☆61Updated this week
- A collection of files related to machine learning force fields☆21Updated 2 years ago
- Code repo of Automated MUltiscale Simulation Environment (AMUSE) for multiscale modeling of heterogenous catalytic reactions☆22Updated 11 months ago