Chi’s Talk on Constructing Accurate Quantitative Structure-Property Relationships via Materials Graph Networks

Chi Chen gave a talk at nanoHub’s Hands-on Data Science and Machine Learning Training Series on how to develop MatErials Graph Network (MEGNet) models for predicting various materials properties from crystal structure. He also demonstrates how the MEGNet framework can be adapted to work with multi-fidelity data sources to improve predictions on high-value small datasets (e.g., experimental data). Extensive examples are shown using Jupyter notebooks. The video is available on the Materials Virtual Lab Youtube Channel.

The megnet package used extensively in these tutorials can be found on Github.