MMunibas / PhysNetLinks
Code for training PhysNet models
☆111Updated 3 years ago
Alternatives and similar repositories for PhysNet
Users that are interested in PhysNet are comparing it to the libraries listed below
Sorting:
- ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.☆152Updated last year
- The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for organic molecules.☆67Updated 3 years ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆83Updated 3 years ago
- Unsupervised learning of atomic scale dynamics from molecular dynamics.☆85Updated 4 years ago
- “Ab initio thermodynamics of liquid and solid water” Bingqing Cheng, Edgar A. Engel, JÖrg Behler, Christoph Dellago and Michele Ceriotti…☆29Updated 5 years ago
- Official implementation of DeepDFT model☆87Updated 2 years ago
- Crystal graph convolutional neural networks for predicting material properties.☆33Updated 3 years ago
- Generate and predict molecular electron densities with Euclidean Neural Networks☆49Updated 2 years ago
- AI-enhanced computational chemistry☆131Updated last month
- Representation Learning from Stoichiometry☆60Updated 3 years ago
- tmQM dataset files☆63Updated 10 months ago
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆59Updated 4 months ago
- Ionic liquid force field parameters (OPLS-2009IL and OPLS-VSIL)☆73Updated last year
- A Python software package for saddle point optimization and minimization of atomic systems.☆129Updated last week
- ☆34Updated last year
- A unified framework for machine learning collective variables for enhanced sampling simulations☆133Updated this week
- Interpolation of molecular geometries through geodesics in redundant internal coordinate hyperspace for complex transformations☆65Updated 11 months ago
- A system for rapid identification and analysis of metal-organic frameworks☆69Updated last month
- Machine Learning Interatomic Potential Predictions☆94Updated last year
- ☆63Updated last year
- A collection of tools and databases for atomistic machine learning☆48Updated 4 years ago
- A collection of Neural Network Models for chemistry☆179Updated last month
- ☆117Updated 3 weeks ago
- molSimplify code☆209Updated this week
- Thermal and photochemical reaction path optimization and discovery☆72Updated last year
- Supporting material for the paper "Data driven collective variables for enhanced sampling"☆20Updated last year
- This is a simple but efficient implementation of PaiNN-model for constructing machine learning interatomic potentials☆24Updated 3 years ago
- code for single-ended and double-ended molecular GSM☆65Updated this week
- Scalable graph neural networks for materials property prediction☆63Updated 2 years ago
- Metadynamics code on the G-space.☆15Updated 2 weeks ago