Sterling G. Baird (sgbaird)

sgbaird

Geek Repo

Company:@AccelerationConsortium (UoT) @sparks-baird (UoU)

Location:Toronto, ON

Home Page:https://acceleration.utoronto.ca/researcher/sterling-baird

Twitter:@SterlingBaird1

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Organizations
AccelerationConsortium
sparks-baird

Sterling G. Baird's repositories

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AMDNet

Code base for AMDNet described in https://doi.org/10.1126/sciadv.abf1754

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Applications

Mathematica packages that I've developed.

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automatminer

An automatic engine for predicting materials properties.

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bounded_pool_executor

Bounded Process&Thread Pool Executor

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CBFV

Tool to quickly create a composition-based feature vector

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chemios

Chemios Framework 👨🏾‍🔬: Accelerating Science through Automation

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Composition-Conditioned-Crystal-GAN

Composition-Conditioned Crystal GAN pytorch code

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conda-smithy

The tool for managing conda-forge feedstocks.

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CrySPY

CrySPY is a crystal structure prediction tool written in Python.

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interp

Interpolate grain boundary properties in a 5 degree-of-freedom sense via a novel distance metric.

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latex-proj-tool

A toolset to traverse and manipulate a Latex project with multiple .tex files.

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LobsterAutomation

This is a package to reproduce the publication on Lobster automation

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maml

Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.

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mat_discover-feedstock

A conda-smithy repository for mat_discover.

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MaterialProperties

Mathematica wrapper to access Materials Project API

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MatGAN

Generative deep learning model for inorganic materials

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modnet

MODNet: a framework for machine learning materials properties

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numba

NumPy aware dynamic Python compiler using LLVM

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ocp

https://opencatalystproject.org/

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pqdm

Comfortable parallel TQDM using concurrent.futures

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pytest-cov

Coverage plugin for pytest.

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pytorch_tabular

A standard framework for modelling Deep Learning Models for tabular data

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simple-blog-bootstrap

This is a template repo you can use to set up a simple blog using GitHub Pages with SSMS Style T-SQL highlighting. Refer to the blog post below for more instructions.

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Sklearn-genetic-opt

Hyperparameters tuning and feature selection, using evolutionary algorithms.

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souschef

Library to easily manipulate conda recipes.

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uncertainty-toolbox

A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

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VickersHardnessPrediction

Predicting load dependent Vickers hardness

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