chgnet

Neural network potential

A neural network potential for atomistic modeling

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

GitHub

255 stars
6 watching
67 forks
Language: Python
last commit: 17 days ago
Linked from 1 awesome list

atomistic-simulationscharge-distributioncharge-transportcomputational-materials-scienceforce-fieldsgraph-neural-networksmachine-learning

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
atomistic-machine-learning/schnetpack A toolbox for training and applying deep neural networks to predict atomistic properties of molecules and materials 792
nngen/nngen Generates hardware-specific accelerator designs for neural networks 340
molcik/python-neuron A Python library for implementing and training various neural network architectures 40
aiqm/torchani A PyTorch implementation of a neural network potential for molecular simulations 466
atomistic-machine-learning/dtnn An open-source Python framework for developing machine learning models to predict quantum-mechanical observables of molecular systems. 77
alexbrillant/multi-layer-perceptron An implementation of a multi-layer neural network in Python, allowing users to train and use the network for classification tasks. 5
neuralegion/shainet A neural network implementation using object-oriented modeling and inspired by biological systems 183
benedekrozemberczki/appnp A PyTorch implementation of a graph neural network model that learns personalized node representations 366
priba/nmp_qc An implementation of neural networks on graph structures for learning molecular properties 339
fengwang/ceras An open-source C++ library for building and training neural networks 120
mhlee0903/multi_channels_pinn Investigating neural networks for drug discovery using multiple chemical descriptors. 3
tkuanlun350/tensorflow-segnet A TensorFlow-based implementation of the SegNet segmentation algorithm, with modifications to address index unravel issues and support multiple features such as dilation and multi-resolution learning. 369
100/cranium A lightweight, portable C implementation of a feedforward artificial neural network library 592
ahmedfgad/neuralgenetic A Python project for training neural networks using the genetic algorithm. 241
codeplea/genann A minimal C library for training and using feedforward artificial neural networks 2,013