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summer_school_intro_to_gmm_and_gps

Jupyter notebook implementations of Gaussian mixture model and Gaussian process written for Machine Learning in Condensed Matter Physics Conference at Donostia International Physics Center (DIPC)

super_material

Calculate superconductor material properties

superconductors-critical-temperature-predictions-regression

:chart_with_upwards_trend: Machine Learning & Data Visualisation/Processing techniques for predicting the critical temperatures required for different superconductors to conduct electrical current with no resistance.

superconductors_regression

Regression analysis on predicting the temperature of superconducting materials

superconml

A semi-supervised learning method to classify superconductors and non-superconductors.

supermat

Superconductors material dataset

supramolecular_vae

swan

An open-source C++ software for efficient nanoscale quantum transport simulations

swot

:school: Identify email addresses or domains names that belong to colleges or universities. Help automate the process of approving or rejecting academic discounts.

syde283-physics-emo

Electricity, Magnetism, and Optics ⚡️

symbolic-regression-utilities

synthetic-x-ray

Research in computational medical physics and deep learning. Conducted at Perelman School of Medicine, UPenn, between April 2020 and December 2020.

tc_superconductors

Predicting critical temperature of Superconductors using multiple linear regression and XGBoost methods

teprop2d

Simple program to calculate thermoelectric properties of 2D materials

thesis-alzheimer

A repo for final project/thesis in medical physics

tlopt

Inverse design of composite metal oxide optical materials

top

Interaction-driven topological superconductivity

topins2

Topological Superconductors - Notebooks for an introductory course

topological-matter-other

Tight-binding systems with topological states (other than Weyl semimetals): topological insulators and other

topological_analysis

Topological analysis for Li local space, site, pathway in crystal structures

transfer-learning-cgcnn

Transfer learning for thermal conductivity (based on CGCNN)

tsne-umap-init

Initialization is critical for preserving global data structure in both t-SNE and UMAP

twod_materials

High throughput workflow tools for characterizing 2D materials in VASP.

uv_us_map

Ultraviolet radiation is an ubiquitous irradiation to human, which is the primary cause of skin cancer.

vasp-catalyst-explorer

voltages-of-battery-electrodes

Using the CGCNN transfer learning model to pridict the voltages of many kinds of metal-ion battery electrodes

vripy

Periodic Voronoi Tesselation of Crystals and Feature Extraction for Quantum Machine Learning in Python

wannier_tools

WannierTools: An open-source software package for novel topological materials. Full documentation:

workshop

The Materials Project Workshop Curriculum

xtal2png

Encode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning models such as Palette.