Faithful novel machine learning for predicting quantum properties
Abstract Machine learning (ML) has accelerated the process of materials classification, particularly with crystal graph neural network (CGNN) architectures. However, advanced deep networks have hitherto proved challenging to build and train for quantum materials classification and property predictio...
| Published in: | npj Computational Materials |
|---|---|
| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Online Access: | https://doi.org/10.1038/s41524-025-01655-w |