Dynamic Topology Reconfiguration of Boltzmann Machines on Quantum Annealers

Boltzmann machines have useful roles in deep learning applications, such as generative data modeling, initializing weights for other types of networks, or extracting efficient representations from high-dimensional data. Most Boltzmann machines use restricted topologies that exclude looping connectiv...

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Detalles Bibliográficos
Autores principales: Liu, Jeremy, Yao, Ke-Thia, Spedalieri, Federico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711444/
https://www.ncbi.nlm.nih.gov/pubmed/33286970
http://dx.doi.org/10.3390/e22111202

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711444/
https://www.ncbi.nlm.nih.gov/pubmed/33286970
http://dx.doi.org/10.3390/e22111202

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