Anthony Onwuli's Projects
LaTeX template for academic CV
AIMNet-NSE model
Github repository for my personal website, forked from mmistakes/minimal-mistakes
Atom2Vec: a simple way to describe atoms for machine learning
atomate2 is a library of computational materials science workflows
The Wren sits on its Roost in the Aviary.
Contains build scripts and instructions for software on a variety of UK HPC resources
A Python package for causal inference in quasi-experimental settings
Pretrained universal neural network potential for charge-informed atomistic modeling
The Impact of Dataset Size on Bayesian Optimization, Insights from the QM9 Dataset
Predict materials properties using only the composition information!
Original implementation of CSPML
doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defect simulation workflow in an efficient, reproducible, user-friendly yet powerful and fully-customisable manner.
An open source python library for scalable Bayesian optimisation.
The Element Movers Distance for chemical composition similarity
A Library for Gaussian Processes in Chemistry
š Everything you need to get started with open source. Hacktoberfest contributions accepted here!
A collection of useful .gitignore templates
A Python package for estimating diffusion properties from molecular dynamics simulations.
This module contains a class for treating kernel mean descriptor (KMD), and a function for generating descriptors with summary statistics. This is an original implementation of KMD.
A collection of notebooks in support of the publication "A Database of Experimentally Measured Lithium Solid Electrolyte Conductivities Evaluated with Machine Learning"
Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
A collection of notebooks to help use some features of the materials project
Graph deep learning library for materials
Data mining for materials science
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
This add-on to pymatgen provides tools for analyzing diffusion in materials.