MaterialsAtlas Model
ALIGNN: Atomistic Line Graph Neural Network
materials sciencedeep learninggraph neural networksmaterials predictionatomistic modelingAImachine learning
The Atomistic Line Graph Neural Network (ALIGNN) is a deep learning model for predicting material properties. It leverages graph neural networks to represent atomic structures and their relationships, enabling accurate property predictions.
Citation: Choudhary, Kamal, and Brian DeCost. "Atomistic line graph neural network for improved materials property predictions." npj Computational Materials 7, no. 1 (2021): 185.
Acknowledgement: Kamal Choudhary & Brian DeCost