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ai4water

framework for developing machine (and deep) learning models for structured data

autoforce

Sparse Gaussian Process Potentials

automatminer

An automatic engine for predicting materials properties.

cgcnn

Crystal graph convolutional neural networks for predicting material properties.

ch485---artificial-intelligence-and-chemistry

CH485 - Artificial Intelligence and Chemistry

chemical-datasets

Python scripts for loading some freely available datasets of molecules and materials.

draw-neural-network

Quick tool to draw fully connected neural network architectures

electrocatalysis-ml

Electrocatalytic integration framework

gdynet

Unsupervised learning of atomic scale dynamics from molecular dynamics.

graph-neural-networks

hexo-theme-3-hexo

hexo主题：三段式设计、极简、方便 Hexo theme: three-stage design

ingrained-lite

An automated framework for fusing materials imaging simulations into experiments.

interpretable-ml-book

Book about interpretable machine learning

intro_to_latex

introduction to LaTeX for beginners

jarvis

JARVIS-Tools: an open-source software package for data-driven atomistic materials design

jarvis-tools-notebooks

A Google-Colab Notebook Collection for Materials Design

lasp

Prototype implementation of Lasp in Erlang.

ludwig

Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

mace

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.

matlantis-contrib

matminer

Data mining for materials science

matminer_examples

A repo of examples for the matminer (https://github.com/hackingmaterials/matminer) code

muhammad-umer

mumerchem.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

pandasgui

A GUI for Pandas DataFrames

pyqt_vasp_stm

python-courses

notebooks for self taught python related courses

seqmetrics

Various errors for tabular/structured/time-series data

sgcnn

Slab graph convolutional neural networks for predicting surface-related material properties

sisso

A data-driven method combining symbolic regression and compressed sensing toward accurate & interpretable models