☆65Dec 9, 2024Updated last year
Alternatives and similar repositories for REANN
Users that are interested in REANN are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ☆21Nov 29, 2021Updated 4 years ago
- Generating Deep Potential with Python☆72Apr 2, 2026Updated last week
- add the influence of external field to REANN model☆26Sep 20, 2024Updated last year
- Advanced ASE Transition State Tools for ABACUS and Deep-Potential☆41Mar 3, 2026Updated last month
- RPMD and rate constant calculations on black-box and machine-learning potential energy surfaces☆16Mar 18, 2026Updated 3 weeks ago
- Deploy open-source AI quickly and easily - Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Program Package for Sampling, Training and Applying ML-based Potential models☆12Apr 7, 2026Updated last week
- REICO-unbiased random sampling to generate diverse datasets encompassing a wide range of atomic configurations and bonding scenarios. EML…☆25Feb 14, 2025Updated last year
- eXtended Equivairant Graph Neural Network☆15Jul 23, 2025Updated 8 months ago
- a package for developing machine learning-based chemically accurate energy and density functional models☆118Apr 28, 2025Updated 11 months ago
- Active Learning for Machine Learning Potentials☆67Feb 3, 2026Updated 2 months ago
- Fast and flexible nonadiabatic molecular dynamics in Julia!☆67Apr 7, 2026Updated last week
- ☆18Nov 19, 2024Updated last year
- MCMC-based algorithm for sampling surface reconstructions☆41Mar 1, 2026Updated last month
- MLP training for molecular systems☆58Updated this week
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- A unified framework for machine learning collective variables for enhanced sampling simulations☆135Updated this week
- ☆30Jul 15, 2025Updated 8 months ago
- SchNetPack - Deep Neural Networks for Atomistic Systems☆914Apr 2, 2026Updated last week
- ☆29Aug 14, 2022Updated 3 years ago
- 2nd generation of the Deep Potential GENerator☆40Updated this week
- Fitting potential energy surface using monomial symmetrization approach☆15Aug 13, 2025Updated 8 months ago
- AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials☆15Jun 30, 2020Updated 5 years ago
- A python script to obtain XYG3-type doubly hybrid (xDH) results using the standard Gaussian xx package (xx=03, 09 and/or 16)☆15Sep 21, 2022Updated 3 years ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆86May 6, 2022Updated 3 years ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Open-source stochastic GW software☆13Apr 28, 2025Updated 11 months ago
- Implementing PaiNN in Pytorch Geometric☆14Mar 10, 2022Updated 4 years ago
- A general purpose library to study vibrational problems using diffusion monte carlo☆17Sep 26, 2024Updated last year
- Create, use, and analyze machine learning potentials within the many-body expansion framework.☆10Sep 4, 2025Updated 7 months ago
- A Python library for building atomic neural networks☆124Mar 26, 2026Updated 2 weeks ago
- ML potentials via transfer learning☆26Mar 29, 2026Updated 2 weeks ago
- NequIP is a code for building E(3)-equivariant interatomic potentials☆890Mar 25, 2026Updated 2 weeks ago
- Accelerating Metadynamics-Based Free-Energy Calculations with Adaptive Machine Learning Potentials☆17Jun 9, 2021Updated 4 years ago
- Automated reaction pathway search for gas-phase molecules☆60Mar 26, 2026Updated 2 weeks ago
- Wordpress hosting with auto-scaling - Free Trial • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆463Sep 27, 2025Updated 6 months ago
- n2p2 - A Neural Network Potential Package☆243Mar 17, 2025Updated last year
- software package for tight-binding DFT calculations on ground and excited states of molecules☆13Feb 13, 2020Updated 6 years ago
- A Newtonian message passing network for deep learning of interatomic potentials and forces☆46Feb 25, 2026Updated last month
- ☆32Nov 10, 2023Updated 2 years ago
- A light-weight PyTorch extension for equivariant deep learning☆18Feb 20, 2025Updated last year
- Interactive tutorials for the PIMD Massive Open Online Course☆24Aug 2, 2023Updated 2 years ago