Active Learning in Bayesian Neural Networks for Bandgap Predictions of Novel Van der Waals Heterostructures
The bandgap is one of the most fundamental properties of condensed matter. However, an accurate calculation of its value, which could potentially allow experimentalists to identify materials suitable for device applications, is very computationally expensive. Here, active machine learning algorithms...
Guardado en:
Autores principales: | Marco Fronzi, Olexandr Isayev, David A. Winkler, Joseph G. Shapter, Amanda V. Ellis, Peter C. Sherrell, Nick A. Shepelin, Alexander Corletto, Michael J. Ford |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Wiley
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/e41b429baf3547a4b1f34b7a6c481518 |
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