Automated stopping criterion for spectral measurements with active learning
Abstract The automated stopping of a spectral measurement with active learning is proposed. The optimal stopping of the measurement is realised with a stopping criterion based on the upper bound of the posterior average of the generalisation error of the Gaussian process regression. It is revealed t...
Guardado en:
Autores principales: | Tetsuro Ueno, Hideaki Ishibashi, Hideitsu Hino, Kanta Ono |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/7d0e960186a94c6d849eea07d0d17fa7 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Automated calculation and convergence of defect transport tensors
por: Thomas D. Swinburne, et al.
Publicado: (2020) -
Bayesian optimization with adaptive surrogate models for automated experimental design
por: Bowen Lei, et al.
Publicado: (2021) -
Automation of diffusion database development in multicomponent alloys from large number of experimental composition profiles
por: Jing Zhong, et al.
Publicado: (2021) -
Ensemble learning-iterative training machine learning for uncertainty quantification and automated experiment in atom-resolved microscopy
por: Ayana Ghosh, et al.
Publicado: (2021) -
Spin–valley Hall phenomena driven by Van Hove singularities in blistered graphene
por: M. Umar Farooq, et al.
Publicado: (2020)