A Python library for building atomic neural networks
☆123Jan 22, 2026Updated last month
Alternatives and similar repositories for PiNN
Users that are interested in PiNN are comparing it to the libraries listed below
Sorting:
- Atoms In Molecules Neural Network Potential☆107Nov 21, 2019Updated 6 years ago
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆460Sep 27, 2025Updated 5 months ago
- JAX-ReaxFF: A Gradient Based Framework for Extremely Fast Optimization of Reactive Force Fields☆74Sep 23, 2024Updated last year
- sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model☆165Jun 13, 2025Updated 8 months ago
- I-ReaxFF: stand for Intelligent-Reactive Force Field☆37Jan 29, 2026Updated last month
- SchNetPack - Deep Neural Networks for Atomistic Systems☆910Feb 22, 2026Updated last week
- AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials☆15Jun 30, 2020Updated 5 years ago
- Tensorflow + Molecules = TensorMol☆277Feb 11, 2021Updated 5 years ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆85May 6, 2022Updated 3 years ago
- Atomic interaction potentials based on artificial neural networks☆126Dec 18, 2025Updated 2 months ago
- Implementing PaiNN in Pytorch Geometric☆14Mar 10, 2022Updated 3 years ago
- eXtended Equivairant Graph Neural Network☆14Jul 23, 2025Updated 7 months ago
- MAISE Module for Ab Initio Structure Evolution (MAISE)☆36Sep 24, 2025Updated 5 months ago
- Coarse-graining library that implements Force-matching☆11Aug 31, 2020Updated 5 years ago
- Electron-passing neural networks for charge partitioning in quantum chemistry☆10Dec 21, 2022Updated 3 years ago
- n2p2 - A Neural Network Potential Package☆241Mar 17, 2025Updated 11 months ago
- ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.☆153Jun 27, 2024Updated last year
- ☆64Dec 9, 2024Updated last year
- Suite of programs to perform non-linear dimensionality reduction -- sketch-map in particular☆48Sep 30, 2024Updated last year
- AutoTST: A framework to perform automated transition state theory calculations☆44Jan 9, 2026Updated last month
- ANI-1 neural net potential with python interface (ASE)☆226Mar 11, 2024Updated last year
- ☆21Nov 29, 2021Updated 4 years ago
- i-PI: a universal force engine☆287Feb 23, 2026Updated last week
- Software for generating machine-learning interatomic potentials for LAMMPS☆182Oct 17, 2025Updated 4 months ago
- Machine Learning Interatomic Potential Predictions☆94Feb 15, 2024Updated 2 years ago
- High-performance operations for neural network potentials☆102Feb 4, 2026Updated last month
- ☆17Jan 2, 2021Updated 5 years ago
- libAtoms/QUIP molecular dynamics framework: https://libatoms.github.io☆383Jan 30, 2026Updated last month
- An interactive structure/property explorer for materials and molecules☆173Feb 23, 2026Updated last week
- Active learning workflow developed as a part of the upcoming article "Machine Learning Inter-Atomic Potentials Generation Driven by Activ…☆28Oct 14, 2021Updated 4 years ago
- Unsupervised learning of atomic scale dynamics from molecular dynamics.☆85Dec 14, 2021Updated 4 years ago
- An open-source Python package for creating fast and accurate interatomic potentials.☆343Feb 6, 2026Updated 3 weeks ago
- A flexible workflow for on-the-fly learning of interatomic potential models.☆33Feb 6, 2026Updated 3 weeks ago
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆463Feb 23, 2026Updated last week
- Python library for advanced atomistic simulations☆23Sep 21, 2017Updated 8 years ago
- pyiron - an integrated development environment (IDE) for computational materials science.☆439Oct 13, 2025Updated 4 months ago
- COMP6 Benchmark dataset for ML potentials☆40Jul 9, 2018Updated 7 years ago
- PROPhet is a code to integrate machine learning techniques with first-principles quantum chemistry approaches☆66Apr 19, 2018Updated 7 years ago
- Deep learning for crystal-structure recognition and analysis of atomic structures☆42Feb 19, 2024Updated 2 years ago