Tools for machine learnt interatomic potentials
☆50Aug 7, 2026Updated this week
Alternatives and similar repositories for janus-core
Users that are interested in janus-core are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- machine learning interatomic potentials aiida plugin☆26Jul 28, 2026Updated last week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆106Jan 28, 2026Updated 6 months ago
- A python library for calculating materials properties from the PES☆149Updated this week
- Heat-conductivity benchmark test for foundational machine-learning potentials☆31Jun 28, 2026Updated last month
- A Python package for the creation of input files for CP2K, MACE-torch, MatterSim, SevenNet, ORB and Grace as well as the post-processing …☆26Jul 31, 2026Updated last week
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Alchemical machine learning interatomic potentials☆36Nov 8, 2024Updated last year
- [ICML'26] Phonon fine-tuning (PFT) and [NeurIPS'25 AI4Mat] Nequix: Training a foundation model for materials on a budget☆76Apr 5, 2026Updated 4 months ago
- Terminal based crystal structure viewer☆15Jun 19, 2026Updated last month
- QUASAR is an autonomous system for end-to-end scientific discovery, integrating LLMs with simulation tools to automate workflows across q…☆18May 26, 2026Updated 2 months ago
- Tensor Atomic Cluster Expansion☆56Updated this week
- ☆47Jul 28, 2026Updated last week
- This is a repository containing an advanced tutorial for jobflow (https://github.com/materialsproject/jobflow) related to computational …☆18Jun 5, 2023Updated 3 years ago
- train and use graph-based ML models of potential energy surfaces☆128Jul 13, 2026Updated 3 weeks ago
- Code for automated fitting of machine learned interatomic potentials.☆157Updated this week
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- ASE framework for Monte Carlo simulations with machine learned interatomic potentials☆28Jul 15, 2026Updated 3 weeks ago
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆105Jul 2, 2026Updated last month
- ☆18Feb 26, 2026Updated 5 months ago
- ⚛ download and manipulate atomistic datasets☆49Nov 25, 2025Updated 8 months ago
- ML Performance and Extrapolation Guide (reference deployment https://ml-peg.stfc.ac.uk)☆55Updated this week
- Library for Crystal Symmetry in Rust☆76Aug 3, 2026Updated last week
- Train, fine-tune, and manipulate machine learning models for atomistic systems☆76Updated this week
- MACE foundation models (MP, OMAT, mh-1)☆287Jul 12, 2026Updated 3 weeks ago
- This repository contains the source code for Bayesian Learned Interatomic Potentials (BLIP)☆34May 4, 2026Updated 3 months ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Phonons from ML force fields☆24Mar 22, 2026Updated 4 months ago
- A unified platform for fine-tuning atomistic foundation models in chemistry and materials science☆82Jun 29, 2026Updated last month
- dataset augmentation for atomistic machine learning☆26Nov 21, 2025Updated 8 months ago
- Training Neural Network potentials through customizable routines in JAX.☆73Jun 30, 2026Updated last month
- A collection of simulation recipes for the atomic-scale modeling of materials and molecules☆54Updated this week
- An ASE-friendly implementation of the amorphous-to-crystalline (a2c) workflow.☆18Oct 19, 2025Updated 9 months ago
- Equitrain: A Unified Framework for Training and Fine-tuning Machine Learning Interatomic Potentials☆29Updated this week
- Machine Learned Interatomic Potential Tools☆25Updated this week
- ☆16Oct 1, 2023Updated 2 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆243Updated this week
- Collection of tutorials to use the MACE machine learning force field.☆71Jul 13, 2026Updated 3 weeks ago
- Compute neighbor lists for atomistic systems☆84Updated this week
- Create atomistic structures with ASE, rdkit and packmol☆27Updated this week
- Some tutorial-style examples for validating machine-learned interatomic potentials☆35Dec 4, 2023Updated 2 years ago
- Repository to host supporting information and code samples for Accelerated DFT☆38Apr 29, 2025Updated last year
- Evaluation of universal machine learning force-fields https://doi.org/10.1021/acsmaterialslett.5c00093☆14Jul 8, 2025Updated last year