Towards overcoming data scarcity in materials science: unifying models and datasets with a mixture of experts framework
Abstract While machine learning has emerged in recent years as a useful tool for the rapid prediction of materials properties, generating sufficient data to reliably train models without overfitting is often impractical. Towards overcoming this limitation, we present a general framework for leveragi...
| Published in: | npj Computational Materials |
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| Main Authors: | , , |
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-11-01
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| Online Access: | https://doi.org/10.1038/s41524-022-00929-x |