sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model
☆168Jun 13, 2025Updated last year
Alternatives and similar repositories for sGDML
Users that are interested in sGDML are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ViRelAy is a visualization tool for the analysis of data as generated by CoRelAy.☆31Apr 30, 2026Updated 3 months ago
- SchNetPack - Deep Neural Networks for Atomistic Systems☆934Aug 2, 2026Updated last week
- CoRelAy is a tool to compose small-scale (single-machine) analysis pipelines.☆32Apr 30, 2026Updated 3 months ago
- Code for training PhysNet models☆117Oct 16, 2022Updated 3 years ago
- A package for density functional approximation using machine learning.☆28Sep 18, 2020Updated 5 years ago
- Proton VPN Special Offer - Get 70% off • AdSpecial partner offer. Trusted by over 100 million users worldwide. Tested, Approved and Recommended by Experts.
- Code for the paper "Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields"☆14Jul 2, 2023Updated 3 years ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆88May 6, 2022Updated 4 years ago
- n2p2 - A Neural Network Potential Package☆245Mar 17, 2025Updated last year
- Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions☆72Sep 17, 2019Updated 6 years ago
- ANI-1 neural net potential with python interface (ASE)☆230Mar 11, 2024Updated 2 years ago
- The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for organic molecules.☆68Apr 11, 2022Updated 4 years ago
- Neural Network Force Field based on PyTorch☆293Jul 13, 2026Updated 3 weeks ago
- i-PI: a universal force engine☆316Updated this week
- Build neural networks for machine learning force fields with JAX☆137Jun 2, 2025Updated last year
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- A Python library for building atomic neural networks☆129Jun 29, 2026Updated last month
- TorchANI 2.0 is an open-source library that supports training, development, and research of ANI-style neural network interatomic potentia…☆554Jul 20, 2026Updated 3 weeks ago
- Explainable AI in Julia.☆118Jul 13, 2026Updated 3 weeks ago
- An open-source Python package for creating fast and accurate interatomic potentials.☆360Jul 7, 2026Updated last month
- Atoms In Molecules Neural Network Potential☆108Nov 21, 2019Updated 6 years ago
- COMP6 Benchmark dataset for ML potentials☆42Jul 9, 2018Updated 8 years ago
- [TMLR 2023] Training and simulating MD with ML force fields☆115Oct 30, 2024Updated last year
- A Newtonian message passing network for deep learning of interatomic potentials and forces☆46Apr 28, 2026Updated 3 months ago
- NequIP is a code for building E(3)-equivariant interatomic potentials☆951Updated this week
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- A deep learning package for many-body potential energy representation and molecular dynamics☆2,004Updated this week
- Python package for extracting representations from state-of-the-art computer vision models☆178Nov 12, 2025Updated 8 months ago
- Input files for Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J. P., Kornbluth, M., ... & Kozinsky, B. (2021). E(3)-equivarian…☆16Jul 3, 2025Updated last year
- Semiempirical Extended Tight-Binding Program Package☆826Updated this week
- libAtoms/QUIP molecular dynamics framework: https://libatoms.github.io☆399Jul 5, 2026Updated last month
- Create, use, and analyze machine learning potentials within the many-body expansion framework.☆10Sep 4, 2025Updated 11 months ago
- Code for performing adversarial attacks on atomistic systems using NN potentials☆41Oct 3, 2022Updated 3 years ago
- Gaussian Approximation Potential Training☆17Jan 22, 2022Updated 4 years ago
- Machine Learning Interatomic Potential Predictions☆93Feb 15, 2024Updated 2 years ago
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- “Ab initio thermodynamics of liquid and solid water” Bingqing Cheng, Edgar A. Engel, JÖrg Behler, Christoph Dellago and Michele Ceriotti…☆36Jun 14, 2020Updated 6 years ago
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆472Apr 18, 2026Updated 3 months ago
- End-To-End Molecular Dynamics (MD) Engine using PyTorch☆715Apr 21, 2026Updated 3 months ago
- Deep Modeling for Molecular Simulation, two-day virtual workshop, July 7-8, 2022☆52Jul 21, 2022Updated 4 years ago
- Training neural network potentials☆480Jul 13, 2026Updated 3 weeks ago
- Allegro is a code for building highly scalable E(3)-equivariant interatomic potentials☆495May 29, 2026Updated 2 months ago
- Tracking citations of atomistic simulation engines☆28Jul 25, 2026Updated 2 weeks ago