Adaptive hyperparameter updating for training restricted Boltzmann machines on quantum annealers

Restricted Boltzmann Machines (RBMs) have been proposed for developing neural networks for a variety of unsupervised machine learning applications such as image recognition, drug discovery, and materials design. The Boltzmann probability distribution is used as a model to identify network parameters...

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Detalles Bibliográficos
Autores principales: Xu, Guanglei, Oates, William S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7851404/
https://www.ncbi.nlm.nih.gov/pubmed/33526868
http://dx.doi.org/10.1038/s41598-021-82197-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7851404/
https://www.ncbi.nlm.nih.gov/pubmed/33526868
http://dx.doi.org/10.1038/s41598-021-82197-1

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