InvarNet: Molecular property prediction via rotation invariant graph neural networks
Predicting molecular properties is crucial in drug synthesis and screening, but traditional molecular dynamics methods are time-consuming and costly. Recently, deep learning methods, particularly Graph Neural Networks (GNNs), have significantly improved efficiency by capturing molecular structures’...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Machine Learning with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S266682702400063X |
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