Incorporating edge convolution and correlative self-attention into graph neural network for material properties prediction

Incorporating edge convolution and correlative self-attention into graph neural network for material properties prediction

The prediction of material properties is a crucial challenge in the design of new materials. Traditional methods based on either trial-and-error experiments or large-scale density functional theory calculations are known to possess various limitations. Although recent machine learning (ML) methods h...

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Bibliographic Details
Main Authors: Zexi Yang, Qi Yu, Yapeng Zhan, Jiying Liu
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Machine Learning: Science and Technology
Subjects:
material property prediction
edge convolution
correlative self-attention
graph convolutional neural network
metal–organic frameworks
Online Access:https://doi.org/10.1088/2632-2153/ad9fcf
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https://doi.org/10.1088/2632-2153/ad9fcf

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