Sparks/Baird Materials Informatics
Sterling Baird and Taylor Sparks Materials Informatics Projects
United States of America
Pinned Repositories
auto-paper
The aim of auto-paper is to give you tips, tricks, and tools to accelerate your publication rate and improve publication quality.
CrabNet
Predict materials properties using only the composition information!
dist-matrix
Fast Numba-enabled CPU and GPU computations of Earth Mover's (scipy.stats.wasserstein_distance) and Euclidean distances.
mat_discover
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
matbench-genmetrics
Generative materials benchmarking metrics, inspired by guacamol and CDVAE.
matsci-opt-benchmarks
A collection of benchmarking problems and datasets for testing the performance of advanced optimization algorithms in the field of materials science and chemistry.
mp-time-split
Use time-splits for Materials Project entries for generative modeling benchmarking.
nomad-examples
Examples of using the Novel Materials Discovery (NOMAD) database, especially downloading all chemical formulas.
self-driving-lab-demo
Software and instructions for setting up and running a self-driving lab (autonomous experimentation) demo using dimmable RGB LEDs, an 8-channel spectrophotometer, a microcontroller, and an adaptive design algorithm, as well as extensions to liquid- and solid-based color matching demos.
xtal2png
Encode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning models such as Palette.
Sparks/Baird Materials Informatics's Repositories
sparks-baird/self-driving-lab-demo
Software and instructions for setting up and running a self-driving lab (autonomous experimentation) demo using dimmable RGB LEDs, an 8-channel spectrophotometer, a microcontroller, and an adaptive design algorithm, as well as extensions to liquid- and solid-based color matching demos.
sparks-baird/auto-paper
The aim of auto-paper is to give you tips, tricks, and tools to accelerate your publication rate and improve publication quality.
sparks-baird/mat_discover
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
sparks-baird/xtal2png
Encode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning models such as Palette.
sparks-baird/matbench-genmetrics
Generative materials benchmarking metrics, inspired by guacamol and CDVAE.
sparks-baird/dist-matrix
Fast Numba-enabled CPU and GPU computations of Earth Mover's (scipy.stats.wasserstein_distance) and Euclidean distances.
sparks-baird/CrabNet
Predict materials properties using only the composition information!
sparks-baird/matsci-opt-benchmarks
A collection of benchmarking problems and datasets for testing the performance of advanced optimization algorithms in the field of materials science and chemistry.
sparks-baird/mp-time-split
Use time-splits for Materials Project entries for generative modeling benchmarking.
sparks-baird/bayes-opt-particle-packing
Compactness Matters: Improving Bayesian Optimization Efficiency of Materials Formulations through Invariant Search Spaces
sparks-baird/CBFV
Tool to quickly create a composition-based feature vector
sparks-baird/chem_wasserstein
A high performance mapping class to construct ElM2D plots from large datasets of inorganic compositions.
sparks-baird/optimization-benchmark
A high-dimensional property predictor framed as a pseudo-materials discovery benchmark with fake compositional (linear) and "no-more-than-X-components" (non-linear) constraints.
sparks-baird/crabnet-hyperparameter
Using Bayesian optimization via Ax platform + SAASBO model to simultaneously optimize 23 hyperparameters in 100 iterations (set a new Matbench benchmark).
sparks-baird/composition-based-stability-regression
Testing out the performance of CrabNet on predicting stability using only compositional features.
sparks-baird/.github
sparks-baird/Ax
Adaptive Experimentation Platform
sparks-baird/cdvae
An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
sparks-baird/gridrdf
Code for calculating grouped representation of interatomic distances (GRID) from crystal structures, and applying this in machine learning models.
sparks-baird/matbench
Matbench: Benchmarks for materials science property prediction
sparks-baird/MLSummerSchoolVienna2022
ESI-DCAFM-TACO-VDSP Summer School on "Machine Learning for Materials Hard and Soft"
sparks-baird/numba
NumPy aware dynamic Python compiler using LLVM
sparks-baird/olympus
Olympus: a benchmarking framework for noisy optimization and experiment planning
sparks-baird/packing-generation
Hard-sphere packing generation with the Lubachevsky–Stillinger, Jodrey–Tory, and force-biased algorithms and packing post-processing.
sparks-baird/Palette-Image-to-Image-Diffusion-Models
Unofficial implementation of Palette: Image-to-Image Diffusion Models by Pytorch
sparks-baird/staged-recipes
A place to submit conda recipes before they become fully fledged conda-forge feedstocks
sparks-baird/techblick-robotics-ai-notes
sparks-baird/tox-debug
sparks-baird/uh2pt-furnace
Ultra-high purity, ultra-high temperature furnace capable of up to 3000 °C
sparks-baird/xtal2png-imagen-pytorch-notebooks
Saving notebooks as I run them, even if I might not end up using them for a manuscript and especially to preserve history when I overwrite them.