Adiabatic Quantum Computation Applied to Deep Learning Networks

Training deep learning networks is a difficult task due to computational complexity, and this is traditionally handled by simplifying network topology to enable parallel computation on graphical processing units (GPUs). However, the emergence of quantum devices allows reconsideration of complex topo...

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Detalles Bibliográficos
Autores principales: Liu, Jeremy, Spedalieri, Federico M., Yao, Ke-Thia, Potok, Thomas E., Schuman, Catherine, Young, Steven, Patton, Robert, Rose, Garrett S., Chamka, Gangotree
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512898/
https://www.ncbi.nlm.nih.gov/pubmed/33265470
http://dx.doi.org/10.3390/e20050380

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512898/
https://www.ncbi.nlm.nih.gov/pubmed/33265470
http://dx.doi.org/10.3390/e20050380

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