Total Magnetization

2 papers with code • 2 benchmarks • 2 datasets

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Libraries

Use these libraries to find Total Magnetization models and implementations
2 papers
97

OQM9HK: A Large-Scale Graph Dataset for Machine Learning in Materials Science

Tony-Y/cgnn Technical report, RIMCS LLC 2022

We introduce a large-scale dataset of quantum-mechanically calculated properties of crystalline materials for graph representation learning that contains approximately 900k entries (OQM9HK).

97
30 Sep 2022

Crystal Graph Neural Networks for Data Mining in Materials Science

Tony-Y/cgnn Technical report, RIMCS LLC 2019

This paper proposes crystal graph neural networks (CGNNs) that use no bond distances, and introduces a scale-invariant graph coordinator that makes up crystal graphs for the CGNN models to be trained on the dataset based on a theoretical materials database.

97
27 May 2019