resnant

dmol-book-japanese

Japanese translation of "Deep learning for molecules and materials book"

XAS-similarity-script

supplementary material

awesome-materials-informatics-research

atomistic-simulation-tutorial

Atomistic simulation hands on tutorial on open neural network potentials

cgcnn

Crystal graph convolutional neural networks for predicting material properties.

crystalview

deep-learning-from-scratch-4

Dreambooth-SD-optimized

Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion

dtreeviz

A python library for decision tree visualization and model interpretation.

ENGE2018

Generative-Deep-Learning-Code-in-Pytorch

The code repository for examples in the O'Reilly book 'Generative Deep Learning' using Pytorch

interpretable-ml-book

Book about interpretable machine learning

Keras-GAN

Keras implementations of Generative Adversarial Networks.

matgl

Graph deep learning library for materials

optuna

A hyperparameter optimization framework

pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project.

resnant.github.io

rookies_exercise

XRM2018

additional materials for XRM2018