.png){kind=icon}
.png){kind=icon}
Return
Exploring data augmentation: Multi-task methods for molecular property prediction
.png){kind=icon}
OA
AI
DOI：10.1016/j.compchemeng.2025.109253.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• Predicting molecular properties with multi-task graph neural networks. • Explored different types of molecular property data augmentation. • Analyzed data augmentation in practical scenarios of molecular data availability. • Recommendations for training of graph neural networks.
Keywords:
Multi-task learning
Molecular property prediction
Graph neural networks
Missing data
Machine learning
Journal
C
IF:
3.9
Papers:
8.1K
Citations:
1.7W